This page tracks remote data engineer openings that are location-eligible for New Hampshire.
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Role Description A dedicated and skilled professional is required to fill the position of Data Entry Specialist at Folium Medical Device. As an essential member of our team, the Data Entry Specialist will play a pivotal role in our organizational operations by updating and maintaining our expansive databases, systems, and platforms. - Accurately input, validate, and maintain a large volume of data in various databases, ensuring that all data is up-to-date and easily accessible. - Regularly review and edit data to eliminate duplication, errors, and inconsistencies. - Collect and gather data from multiple sources, analyzing them for patterns and trends that could improve our operational efficiency and effectiveness. - Collaborate with team members across the organization to understand their data needs and ensure they receive accurate and timely reports. - Conduct system tests and troubleshooting to resolve data, system, and performance issues. - Maintain data privacy, complying with company policies and applicable laws. Qualifications - At least 2 years of proven work experience in a data entry role, preferably in the healthcare industry. - Proficient with MS Office Suite (particularly Excel) and database systems. - Strong ability to type swiftly and accurately. - Excellent attention to detail with the ability to spot numerical errors. - Ability to multitask, prioritize tasks, and meet deadlines. - Good communication and collaboration skills, able to work with various team members across the company. - A high school degree or equivalent; further education in a relevant field is a plus. Benefits - Opportunity to work in a dynamic and innovative healthcare technology company. - Competitive salary package, including health insurance and retirement benefits. - Professional and personal growth through skills development programs and education opportunities. - Folium values work-life balance with flexible working hours and paid time off. - A diverse and inclusive culture, making Folium a great place to work.
Solving big problems, building trust in society, and empowering our clients to shape the future.
• Support the design and development of an enterprise Contract Performance Analytics platform for a large healthcare system • Focus on data architecture, ELT/ETL pipeline development, and integration of clinical, claims, and operational data into a scalable analytics ecosystem • Build a unified data system that enables insights across value-based care contracts (MSSP, Medicare Advantage, Commercial, and Employer Health Plans) • Integrate EHR cloud-based data processing and an enterprise data warehouse to support analytics and reporting • Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load healthcare data from diverse structured and unstructured sources • Develop pipelines to process data from CMS and payer files (CCLF, paid claims, PUG) as well as Epic (Caboodle, Clarity) data models and extracts • Build and optimize data models to support analytics, reporting, and operational use cases, including BI and downstream analytics consumption • Transform raw data into standardized, analytics-ready canonical data models and curated data marts • Build lakehouse/medallion architecture, data ingestion patterns, and orchestration frameworks • Implement and maintain CI/CD pipelines for data engineering workflows, including pipelines and scheduled jobs, using version control and automation tools • Collaborate with database administrators, analysts, and application teams to integrate data sources, design schemas, and support downstream data consumers • Ensure data quality, integrity, and accuracy through validation, monitoring, logging, and alerting • Support data migration, integration, and modernization initiatives, including legacy system upgrades, optimization of large-scale ETL pipelines, query performance, and cloud adoption efforts • Troubleshoot and resolve issues in development and production environments to maintain stable and reliable data pipelines • Document data flows, pipelines, test cases, and technical solutions to support knowledge sharing and compliance requirements • Stay current with emerging tools, technologies, and best practices in data engineering and cloud platforms
Henry Schein started out as a Queens, New York-based pharmacy in 1932 and is now a Fortune 500 company specializing in healthcare products and solutions for hea
• Define and implement a scalable, enterprise-wide data architecture aligned with business and technology goals • Develop a data strategy roadmap, ensuring long-term sustainability, scalability, and efficiency • Partner with executive leadership, product teams, and engineering to ensure data initiatives drive business value • Establish enterprise data governance, security, and compliance frameworks leveraging tools like Collibra or Alation • Oversee the design and evolution of data lakes, data warehouses, and cloud-based analytics platforms using Databricks, Snowflake, BigQuery, or Redshift • Lead the adoption of modern data architecture patterns, including event-driven architectures, real-time data streaming (Kafka, Pulsar), and AI-driven analytics • Provide guidance on database optimization, indexing, partitioning, and storage strategies for tools like PostgreSQL, MySQL, and NoSQL solutions like MongoDB or Cassandra • Evaluate emerging technologies, making recommendations for tools and platforms that enhance data capabilities • Direct ETL/ELT strategies, ensuring seamless data flow across systems with Python, Apache Airflow, dbt, or Informatica • Architect cloud-based solutions (AWS, Azure, or GCP) using services such as AWS Glue, Azure Synapse, and Google Cloud Dataflow to support analytics, AI, and operational use cases • Ensure API-first design for data integration using GraphQL, RESTful APIs, or event-driven architectures (Kafka, AWS Kinesis, Pub/Sub) • Define and oversee data quality, lineage, and cataloging efforts using Great Expectations, Monte Carlo, or DataHub • Develop policies for data privacy, access control, and encryption, ensuring compliance with GDPR, CCPA, HIPAA, or other relevant regulations • Implement enterprise-wide metadata management and data lineage tracking using Collibra, Alation, or Data Catalog solutions • Drive best practices for data security and compliance audits, leveraging IAM tools and cloud security solutions • Lead a team of data architects, engineers, and analysts, mentoring them on best practices • Act as a liaison between business and technical teams, translating business needs into scalable data solutions • Champion a culture of innovation, ensuring the data team is adopting cutting-edge methodologies • Conduct data architecture reviews, ensuring alignment with organizational standards
Jellyfish, also known as Orthogonal Networks, Inc., is self-described as a pioneer in engineering management platforms (EMPs). Founded with the mission to help
Staff Data Architect Location: Remote - US Full time Department: Engineering Compensation - $200K – $260K • Offers Equity The posted range represents the possible base pay for this role. Actual compensation will depend on your experience, skills, role scope, and alignment with the position. Some postings may include more than one salary band to reflect different levels. Jellyfish is the backbone for elite engineering organizations, and our data infrastructure needs to be as high-performing and insightful as the teams we serve. We are looking for a Staff/Lead Data Architect to help us design, automate, and scale the next generation of our Jellyfish data platform. You’ll be responsible for maturing our core data models, automating environment boundaries, and driving advanced observability and cost-attribution deeper into our data pipeline architecture. If you view manual data intervention as a technical debt to be solved and want to work in an environment where your architectural decisions directly impact how the world’s best engineering leaders measure their productivity, you’re the perfect fit. What you’ll actually be doing: - Architectural Evolution & Blueprinting – You’ll own the blueprint for the next-generation Jellyfish data platform. You'll tackle our existing data footprint, refactoring pipelines and structures into highly efficient, scalable patterns (like Medallion-style schemas or unified semantic layers). - Automated Data Governance – You’ll design and automate strict, code-driven environment isolation boundaries. You'll ensure dev, staging, and production data catalogs (and their underlying cloud storage) never dangerously cohabitate, eliminating the risk of "fat-finger" data drops or PII leakage. - Orchestration & Compute Scaling – You’ll lead the modernization of our workflow orchestration and distributed compute engines. You’ll focus on slashing engine runtime overhead, eliminating API bottlenecks, and streamlining heavy parallelized or mapped data tasks. - Modern Integration Middleware – You'll partner with application teams to ensure our React frontends and backend services hit highly secure, cached API and Backend-for-Frontend (BFF) layers rather than querying raw data services directly, protecting our warehouses from concurrency spikes. - Proactive Data Observability & FinOps – You’ll build and maintain granular data-quality monitors and cost-allocation frameworks. You won't just track overall warehouse spend; you’ll implement systems to map execution cost and token usage directly down to the tenant, team, or user level. You’re a great fit if: - Data Tooling Fluency – You have deep, production-level experience with Python, advanced SQL, and modern data stack essentials. You are deeply familiar with programmatic orchestrators (like Prefect, Dagster, or Airflow) and modern data validation engines (like Pydantic v2). - Catalog & Warehouse Practitioner – You have hands-on mastery of enterprise-scale data platforms and governance layers (e.g., Snowflake, Databricks Unity Catalog, BigQuery) and know exactly how to map environments to catalogs and data quality to schemas. - Automation Mindset – You look at a manual data backfill or a clicked-together database permission and immediately think about how to automate it via Infrastructure-as-Code (Terraform) or programmatic workflows. - Collaborative Systems Thinker – You don’t design in a vacuum. You are excellent at documenting data lineage, mentoring data engineers, and collaborating across DevOps and Product teams to align infrastructure with business goals. - Pragmatic Problem Solver – You know the difference between data quality stages and software development lifecycles. You know when a "perfect" distributed cluster is required and when a "good enough" cached view keeps the business moving. Bonus Points: - You’ve survived (and thrived in) a rapidly scaling B2B SaaS startup handling massive multi-tenant data sets. - You have strong opinions on the future of Git-like data versioning and zero-copy cloning (e.g., Iceberg, Nessie). - You’ve managed complex cloud-billing attributions or scaled heavy LLM/vector-embedding data workloads and lived to tell the tale. A list of job experiences and qualification requirements is great, but humility, a performance-driven attitude, and a team-player approach are most important to us. We love to have fun and win in the process. We only hire people who have a passion for building great companies in an environment where a sense of humor is a must. Occasional travel may be required. Applicants must be authorized to work for any employer in the US. We are unable to sponsor or take over sponsorship of an employment visa at this time. Let’s talk about us! This is all about you, but you want to know a little about us. Jellyfish enables leaders to effectively build AI-integrated engineering teams, align engineering decisions with business initiatives and deliver the right software efficiently and on time. AI tools alone won’t transform your org—Jellyfish shows you what’s working, what’s not, and how to build high-performing teams that know how to use AI the right way.
Jellyfish, also known as Orthogonal Networks, Inc., is self-described as a pioneer in engineering management platforms (EMPs). Founded with the mission to help
Senior Data Engineer Location: Remote - US Full time Department: Engineering Compensation - $190K – $240K • Offers Equity The posted range represents the possible base pay for this role. Actual compensation will depend on your experience, skills, role scope, and alignment with the position. Some postings may include more than one salary band to reflect different levels. Jellyfish is the backbone for elite engineering organizations, and our data pipelines need to be as high-performing and reliable as the teams we serve. We are looking for a Senior Data Engineer to help us build, automate, and execute the next generation of our Jellyfish data platform. Working closely with our Lead Data Architect, you’ll be responsible for implementing core data models, building production-grade CI/CD for data pipelines, and transforming raw engineering signals into highly optimized analytical layers. If you view broken pipelines and manual data patches as a technical debt to be solved and want to write code that directly impacts how the world’s best engineering leaders measure their output, you’re the perfect fit. What you’ll actually be doing: - Pipeline Execution & Modeling – You’ll maintain our end-to-end data pipelines, writing clean, modular Python and SQL. You will help translate the architectural blueprint into reality, structuring data across our Medallion layers (Bronze > Silver > Gold) for maximum performance and reliability. - Orchestration Modernization – You’ll take the lead on migrating, optimizing, and maintaining our workflow orchestration engines. You’ll eliminate pipeline bottlenecks, leverage modern fast-paths (like Pydantic v2 and async database clients), and ensure distributed tasks scale seamlessly without hitting API limits. - Data CI/CD & Infrastructure Automation – You’ll build the "paved road" for data deployments. You’ll use Terraform to provision data resources and write automated tests to validate schemas and data quality before code ever hits our isolated staging or production catalogs. - API & Caching Integration – You’ll collaborate with product developers to expose data safely. You’ll help design and optimize the application backend tiers, backend-for-frontend (BFF) layers, and Redis caching structures that protect our core data warehouse from frontend concurrency spikes. - On-Call & Observability Triage – You’ll participate in the data platform's incident response rotation. You won't just patch a failing pipeline; you’ll build deep observability, refine alerts to reduce noise, and write programmatic fixes to ensure the issue never happens again. You’re a great fit if: - Data Engineering Fluency – You have solid, production-level experience with Python, advanced SQL, and data transformation frameworks (like dbt or PySpark). You are highly comfortable working with programmatic orchestrators (such as Prefect, Dagster, or Airflow). - Warehouse & Catalog Practitioner – You know your way around enterprise data platforms (e.g., Snowflake, Databricks, BigQuery). You understand how to safely navigate environment boundaries, manage access keys securely, and write performant queries that don't balloon the cloud bill. - Automation Mindset – You look at a repeated data backfill, a manual schema fix, or an untracked data quality bug and immediately think about how to script a permanent, automated solution. - Collaborative Builder – You love working in a team. You write readable code, value thorough documentation and clear data lineage, and enjoy collaborating with application engineers to solve complex data delivery problems. - Pragmatic Problem Solver – You know when to write a perfectly optimized distributed processing job and when a simple, well-indexed database table or cached view is the smartest move to keep the business moving. Bonus Points: - You’ve survived (and thrived in) a rapidly scaling startup handling complex, multi-tenant B2B SaaS data. - You have strong opinions on data quality testing frameworks (like Great Expectations or Soda) and data-observability patterns. - You’ve worked extensively with cloud cost allocation or tracked token-level spend for LLM/AI model integrations. A list of job experiences and qualification requirements is great, but humility, a performance-driven attitude, and a team-player approach are most important to us. We love to have fun and win in the process. We only hire people who have a passion for building great companies in an environment where a sense of humor is a must. Occasional travel may be required. Applicants must be authorized to work for any employer in the US. We are unable to sponsor or take over sponsorship of an employment visa at this time. Let’s talk about us! This is all about you, but you want to know a little about us. Jellyfish enables leaders to effectively build AI-integrated engineering teams, align engineering decisions with business initiatives and deliver the right software efficiently and on time. AI tools alone won’t transform your org—Jellyfish shows you what’s working, what’s not, and how to build high-performing teams that know how to use AI the right way.
Jellyfish, also known as Orthogonal Networks, Inc., is self-described as a pioneer in engineering management platforms (EMPs). Founded with the mission to help
Data Engineer Location: Remote - US Full time Department: Engineering Pay: $165K – $205K + Equity The posted range represents the possible base pay for this role. Actual compensation will depend on your experience, skills, role scope, and alignment with the position. Some postings may include more than one salary band to reflect different levels. Jellyfish is the backbone for elite engineering organizations, and our data pipelines need to be as high-performing and reliable as the teams we serve. We are looking for a Data Engineer to join our data platform team and help us execute, automate, and maintain the next generation of our Jellyfish data platform. In this role, you’ll be a core builder—fully autonomous, highly proficient, and responsible for translating architectural blueprints into clean, production-grade pipelines. If you view manual data patches and unmonitored workflows as bugs to be squashed and want to write code that directly impacts how the world’s best engineering leaders measure their output, you’re the perfect fit. What you’ll actually be doing: - Core Pipeline Engineering – You’ll write the clean, modular Python and optimized SQL that drives our daily data transformations. You will be responsible for implementing our Medallion-layer data models (Bronze → Silver → Gold), ensuring high performance and data integrity. - Modern Orchestration & Tuning – You’ll manage and tune our workflow orchestration engines (like Prefect or Dagster). You’ll hunt down slow execution paths, optimize parameter serialization (e.g., leveraging Pydantic v2), and ensure our distributed processing jobs run efficiently. - Infrastructure as Code (IaC) – You won't just write data scripts; you'll own your infrastructure deployment. You will use Terraform to manage and provision data warehouse schemas, permissions, and tables across securely isolated staging and production catalogs. - API & Caching Integration – You’ll collaborate with product developers to expose data safely. You’ll help implement and maintain the application backend tiers, backend-for-frontend (BFF) layers, and Redis caching structures that protect our core data warehouse from frontend concurrency spikes. - On-Call & Pipeline Observability – You’ll participate in our data platform's incident response rotation. When a pipeline breaks, you won't just fix the data; you’ll refine the Datadog dashboards and alerts to ensure we catch the issue earlier next time. You’re a great fit if: - Data Engineering Fluency – You have solid, hands-on production experience with Python, advanced SQL, and data transformation concepts. You are comfortable building and scheduling workflows using programmatic orchestrators (such as Prefect, Dagster, or Airflow). - Warehouse & Catalog Practitioner – You know your way around enterprise data platforms (e.g., Snowflake, Databricks, BigQuery). You understand how to navigate environment boundaries, manage access keys securely, and write performant queries. - Automation Mindset – You look at a repeated data backfill, a manual schema fix, or an untracked data quality bug and immediately think about how to script a permanent, automated solution. - Collaborative Builder – You love working in a team. You write readable code, value thorough documentation and clear data lineage, and enjoy collaborating with application engineers to solve complex data delivery problems. - Pragmatic Problem Solver – You know when to write a perfectly optimized distributed processing job and when a simple, well-indexed database table or cached view is the smartest move to keep the business moving. Bonus Points: - You’ve worked in a rapidly scaling startup handling complex, multi-tenant B2B SaaS data. - You have experience with data quality testing frameworks (like Great Expectations or Soda). - You’ve interacted with cloud cost allocation tracking or token-level spend for LLM/AI model integrations. A list of job experiences and qualification requirements is great, but humility, a performance-driven attitude, and a team-player approach are most important to us. We love to have fun and win in the process. We only hire people who have a passion for building great companies in an environment where a sense of humor is a must. Occasional travel may be required. Applicants must be authorized to work for any employer in the US. We are unable to sponsor or take over sponsorship of an employment visa at this time. Let’s talk about us! This is all about you, but you want to know a little about us. Jellyfish enables leaders to effectively build AI-integrated engineering teams, align engineering decisions with business initiatives and deliver the right software efficiently and on time. AI tools alone won’t transform your org—Jellyfish shows you what’s working, what’s not, and how to build high-performing teams that know how to use AI the right way.
Role Description We are looking for a Staff Data Engineer with significant experience to join our data team. Our data platform powers analytics for both internal business users and external customers, and plays a key role in enabling data-driven decision-making across the organization. In this role, you will focus on evolving our existing data platform and investing in its reliability, performance, and scalability. You will work closely with internal stakeholders to design and implement new data models in our Enterprise Data Warehouse as new reporting and analytics requirements emerge. The platform currently supports data and analytics needs across Checkfront, Manifest, Regiondo, and Rezdy, and provides reporting capabilities for both operational teams and customers. Our modern data stack includes Google BigQuery, Fivetran, dbt, Metabase, and GoodData. This is a great opportunity for someone who enjoys working with mature data platforms, improving existing pipelines, and delivering high-quality analytics that directly support business outcomes. This is a remote position working primarily Pacific Time hours in Canada or the United States. What you will do - Architect and evolve our data platform for scale and reliability - Define and implement advanced platform engineering test practices, including automated data integrity checks and CI/CD pipelines to ensure data quality - Act as a technical leader and mentor for the data engineering team, setting standards for system design and platform reliability - Maintain and support the enterprise data platform and existing data pipelines - Ensure reliable data ingestion, transformation, and reporting across Checkfront, Manifest, Regiondo, and Rezdy - Monitor, troubleshoot, and resolve issues across the data stack to ensure data accuracy and availability - Work closely with internal business users to understand their reporting and analytics requirements - Design and implement new data models in BigQuery using dbt based on business needs - Maintain and manage data ingestion pipelines - Deliver clean, well-structured datasets that power reporting and dashboards in GoodData or Google Sheets - Optimize BigQuery queries and data models for performance and cost efficiency - Ensure data quality, documentation, and governance across the data platform - Set up a testing and validation framework to automatically ensure data integrity across the platform - Contribute to data platform monitoring, alerting, and platform reliability Qualifications - Significant experience designing, building, and operating high-scale, distributed data platforms - Strong experience with SQL and data modeling in modern cloud data warehouses - Hands-on experience with Google BigQuery - Experience using dbt for transformation and data modeling - Experience with data ingestion tools such as Fivetran or similar ELT platforms - Experience supporting analytics platforms or BI tools - Strong understanding of data warehousing concepts and dimensional modeling - Expertise in maintaining and operating production data pipelines and platforms - Ability to work with business stakeholders to translate requirements into scalable data models - Strong troubleshooting and problem-solving skills - Excellent communication and documentation skills - Proven track record of mentoring engineers and improving technical standards - Experience leading large-scale architectural migrations - Ability to influence cross-functional roadmaps and communicate complex technical concepts Benefits - High trust, real impact: You’ll have the autonomy and expectation to lead with ownership, tackle problems end-to-end, and make decisions that move the business forward in meaningful ways - Curiosity with discipline: We value asking sharp questions, challenging assumptions, and exploring smarter ways to work - One team, all in: Collaboration beats ego, wins are shared, and we rally together when the work gets tough - Space to grow: You’ll be supported and stretched, taking on challenges that build capability, sharpen judgment, and accelerate your growth as a leader and problem-solver - Progress with purpose: We move fast, stay focused on what truly matters, and prioritize long-term impact over quick fixes
Harnessing the power of diversity, expertise, and innovation to transform lives, accelerate equity, and create lasting.
• Oversee the design, development, and implementation of data management, reporting, workflow automation, and system integration solutions that support Head Start and Early Head Start programs • Lead data projects, infrastructure, and automation initiatives to improve grant administration, operational efficiency, data quality, and decision-making while ensuring systems are scalable, secure, and reliable • Provide technical leadership, project oversight, and continuous improvement efforts to deliver innovative data solutions that support organizational performance and improve outcomes for children and families • Manage complex data engineering projects from planning through deployment, ensuring solutions are scalable, secure, reliable, and aligned with business requirements • Design and maintain data pipelines, ETL processes, databases, data warehouses, and reporting systems • Develop and manage API integrations and automated workflows across multiple systems and platforms • Establish and enforce data governance, data quality, security, and compliance standards • Collaborate with stakeholders to gather requirements and translate business needs into technical solutions • Monitor system performance, troubleshoot issues, and implement process and technology improvements • Prepare technical documentation, reports, and presentations for leadership and stakeholders
Tempus Labs, commonly known as Tempus, is a technology company based in Chicago, Illinois, that is working to advance data-driven precision medicine by practica
Passionate about precision medicine and advancing the healthcare industry? Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time. Responsibilities: - Collaborate with cross-functional teams including medical oncologists, research scientists, and engineers to develop and maintain clinical data models. - Translate customer needs and product requests into key concept definitions and business logic for complex models. - Facilitate integration of data model into workflows, applications, and data deliveries. - Structure and normalize data from a variety of sources, including Tempus curated data, EHR integrations, and lab systems. - Develop and maintain knowledge bases for clinical concepts. - Create and execute validation plans in conjunction with SMEs for new models and disease types. - Proactively monitor and support quality assurance and process improvement initiatives. - Monitor performance of production processes and recommend areas for improvement. Qualifications: - 5+ years of oncology data modeling experience. - Experience working with real world data from various sources (e.g., curation workflows, EHRs, lab systems, claims, research datasets). - Experience working with modern ELT tools such as DBT to maintain high volume, high velocity data warehouses - Experience working with standard medical terminologies (e.g., SNOMED CT, RxNorm, LOINC, ICD-9/10). Nice-to-haves: - Clinical background (MD/DO, PharmD, PA, NP, RN, etc.). - Familiarity with next-generation sequencing data. - Experience with real world data analysis in Python or R. - Participation in professional organizations (e.g., OHDSI, AMIA). #LI-BL1 We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
BDR Solutions, LLC, (BDR) supports the U.S. Federal Government in successfully achieving its mission and goals. Our service and solution delivery starts with understanding each client’s end-state, and then seamlessly integrating within each Agency’s organization to improve and enhance business and technical operations and deployments. (Military Veterans are highly encouraged to apply)
Role Description BDR Solutions is looking for a data management intern who is eager to gain hands-on experience and practical skills, as well as to explore career paths. You will be working closely with a designated team to: - Become familiar and learn data management platforms (similar to Snowflake, Palantir, Databricks, etc). - Capture and manage data requirements. - Develop data ontology and data pipelines. - Support process improvement efforts. - Attend meetings and take minutes as required. - Address other duties as assigned. This intern position will be focused on supporting specific corporate activities including but not limited to: Operations and Growth. This will provide you with an opportunity to learn about the function of the specific area to see if it may be the right career path for you. Some of the responsibilities will include, but are not limited to: - Research and data gathering, analysis, and reconciliation. - Process and workflow improvement — mapping and optimizing task sequences to reduce time and errors. - Automation and data platform support — assisting with data pipelines and ontology/data mapping on modern data management platforms. - Electronic file organization, document review, and editing. - Support corporate and other functions as needed. - Other duties as assigned. Qualifications - Eager to learn and work with various departments in the company. - Flexible to accommodate diversity in daily tasks. - Ability to commit a minimum of 40 hours per month, mostly scheduled in increments of 10 hours per week. - Proficiency in the MS Office Suite with an aptitude to learn. - Excellent written and oral communication skills. - Ability to work remotely from a quiet and uninterrupted place with a high degree of accountability. Requirements - Background in computer science, engineering, or a related technical field. - Hands-on experience with Python and SQL. - Detail-oriented, with the ability to effectively document and communicate details. - Computer/Laptop to use in the performance of position. (If not available, BDR can provision one.) - Excellent attention to detail and willingness to learn new skills, new client environments, and grow domain expertise. - Veteran. - U.S Citizenship is required. Benefits - Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, marital status, disability, veteran status, sexual orientation, or genetic information.
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SQL, Python, BigQuery, Airflow, Terraform, Observability/Monitoring
