This page tracks remote data engineer openings that are location-eligible for Oregon.
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• Design, build, and own the data pipelines that move and transform data from our application and third-party sources into relational databases - keeping them reliable and well-modeled as volume and complexity grow • Partner with analytics engineering to build the data models and reporting that give researchers and teams real visibility into how their work is performing • Own data quality as a first-class concern across ingestion, modeling, and reporting. Catch problems before they reach a model, a dashboard, or a user, and fix them • Build and ship production AI systems the data infrastructure and services that ML features run on • Design and own evaluation systems that tell us whether an AI feature is ready to ship and holding up over time: eval harnesses, test datasets, and production monitoring built as software, not one-off analyses • Set the standard for how data work gets done. Write clearly, share context early, and make the people around you faster
Role Description The Senior Data Engineer role at Spring Venture Group is an opportunity to work at the intersection of data pipelines, data modeling, analytics, AI/ML enablement, and modern cloud-native platforms, with Snowflake as your foundation. We are looking for someone who is excited to move away from building every pipeline from scratch and toward designing data products and AI-powered applications. As automation and platform capabilities advance, you will evolve from a traditional builder into a strategic architect of data-driven solutions. Essential Duties - Modern Data Platform & AI Enablement - Build advanced data pipelines utilizing the Medallion Architecture to create high-quality data sources in Snowflake. - Leverage AI-assisted development tools to reduce manual pipeline work and explore emerging Snowflake capabilities like Cortex to support AI/ML-enabled workflows. - Build Data Applications that contribute to interactive experiences, including Streamlit-based apps, transforming Snowflake from a warehouse into a full-service data platform. - Create robust data pipelines using AWS technologies to serve specific business needs. - Data Modeling & Business Impact - Design and evolve analytical data models that support BI, advanced analytics, and AI workloads. - Partner directly with Analytics and Data Science teams to translate complex business questions into well-structured, modular data assets. - Write complex Python/SQL scripts and stored procedures to ensure 99.95% uptime and optimize query performance for downstream consumption. - Leadership & Engineering Excellence - Serve as a primary advisor to the Data Management team to identify opportunities for technical improvements and automation. - Act as a leader for junior and mid-level engineers, providing direction on programming best practices, query optimization, and business tact. - Architect replacements for legacy systems with a focus on data governance and maintainable documentation, including flowcharts and clear code comments. - Support after hours and weekend releases from our internal Software Development teams. - Actively participate in code review and weekly technicals with another more senior engineer or manager. - Assist departments with time-critical SQL execution and debug database performance problems. Qualifications - Bachelor's degree in Computer Science, or a related technical field. - 4-5 years of practical production work in Data Engineering. - Expertise of the Python programming language. - Expertise of Snowflake. - Expertise of SQL, databases, & query optimization. - Must have experience in a large cloud provider such as AWS, Azure, GCP. - Advanced at reading code independently and understanding its intent. - Advanced at writing readable, modifiable code that solves business problems. - Ability to construct reliable and robust data pipelines to support both scheduled and event-based workflows. - Working directly with stakeholders to create solutions. - Mentoring junior and mid-level engineers on best practices in programming, query optimization, and business tact. Preferred Experience - Experience building or supporting Streamlit applications or similar data-driven apps. - Familiarity with Snowflake Openflow for data ingestion and orchestration. - Exposure to Snowflake Cortex or AI/ML-enabled analytics workflows. - Background in analytics engineering (dbt-style modeling, semantic layers, metrics design). Benefits - Competitive compensation. - Medical, Dental and Vision benefits after a short waiting period. - 401k matching program. - Generous paid time off program with an additional company break during the holidays. - Annual Volunteer Time Off (VTO) and a donation matching program. - Life Insurance. - Employee Assistance Program (health & well-being on and off the job). - Rewards and Recognition. - Maternity and Parental Leave. - Training program and ongoing support throughout your entire Spring Venture Group career. - Diverse, inclusive & welcoming culture. - Optional enrollment options include HSA/FSA, AD&D, Spousal/Dependent life insurance, Short Term/Long Term Disability, Travel Assist, and Legal plans.
Role Description The Senior Data Engineer role at Spring Venture Group is an opportunity to work at the intersection of data pipelines, data modeling, analytics, AI/ML enablement, and modern cloud-native platforms, with Snowflake as your foundation. We are looking for someone who is excited to move away from building every pipeline from scratch and toward designing data products and AI-powered applications. As automation and platform capabilities advance, you will evolve from a traditional builder into a strategic architect of data-driven solutions. Essential Duties - Modern Data Platform & AI Enablement - Build advanced data pipelines utilizing the Medallion Architecture to create high-quality data sources in Snowflake. - Leverage AI-assisted development tools to reduce manual pipeline work and explore emerging Snowflake capabilities like Cortex to support AI/ML-enabled workflows. - Build Data Applications that contribute to interactive experiences, including Streamlit-based apps, transforming Snowflake from a warehouse into a full-service data platform. - Create robust data pipelines using AWS technologies to serve specific business needs. - Data Modeling & Business Impact - Design and evolve analytical data models that support BI, advanced analytics, and AI workloads. - Partner directly with Analytics and Data Science teams to translate complex business questions into well-structured, modular data assets. - Write complex Python/SQL scripts and stored procedures to ensure 99.95% uptime and optimize query performance for downstream consumption. - Leadership & Engineering Excellence - Serve as a primary advisor to the Data Management team to identify opportunities for technical improvements and automation. - Act as a leader for junior and mid-level engineers, providing direction on programming best practices, query optimization, and business tact. - Architect replacements for legacy systems with a focus on data governance and maintainable documentation, including flowcharts and clear code comments. - Support after hours and weekend releases from our internal Software Development teams. - Actively participate in code review and weekly technicals with another more senior engineer or manager. - Assist departments with time-critical SQL execution and debug database performance problems. Qualifications - Bachelor's degree in Computer Science, or a related technical field. - 4-5 years of practical production work in Data Engineering. - Expertise of the Python programming language. - Expertise of Snowflake. - Expertise of SQL, databases, & query optimization. - Must have experience in a large cloud provider such as AWS, Azure, GCP. - Advanced at reading code independently and understanding its intent. - Advanced at writing readable, modifiable code that solves business problems. - Ability to construct reliable and robust data pipelines to support both scheduled and event-based workflows. - Working directly with stakeholders to create solutions. - Mentoring junior and mid-level engineers on best practices in programming, query optimization, and business tact. Preferred Experience - Experience building or supporting Streamlit applications or similar data-driven apps. - Familiarity with Snowflake Openflow for data ingestion and orchestration. - Exposure to Snowflake Cortex or AI/ML-enabled analytics workflows. - Background in analytics engineering (dbt-style modeling, semantic layers, metrics design). Benefits - Competitive compensation. - Medical, Dental and Vision benefits after a short waiting period. - 401k matching program. - Generous paid time off program with an additional company break during the holidays. - Annual Volunteer Time Off (VTO) and a donation matching program. - Life Insurance. - Employee Assistance Program (health & well-being on and off the job). - Rewards and Recognition. - Maternity and Parental Leave. - Training program and ongoing support throughout your entire Spring Venture Group career. - Diverse, inclusive & welcoming culture. - Optional enrollment options include HSA/FSA, AD&D, Spousal/Dependent life insurance, Short Term/Long Term Disability, Travel Assist, and Legal plans.
• Define and evolve the Accelerant Data Platform by gathering stakeholder requirements. • Identify opportunities to deliver value through data-driven solutions enabling Risk Exchange efficiency. • Collaborate with Product Managers, Engineers, and Designers to deliver high-quality solutions. • Develop and own roadmap for data ingestion and consumption with Outcome and Key Results (OKRs). • Communicate strategy and platform outcomes to various levels within the company.
Improving people’s lives by harnessing the healthcare data explosion through an intelligent data integration platform.
• Architect Enterprise‑Scale Data Solutions: Design, build, and evolve high‑volume batch and real‑time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks. • Own Platform‑Level Integrations: Develop end‑to‑end ingestion and transformation frameworks integrating Databricks, Snowflake, AWS services (such as S3, SQS, Lambda), and external data provider APIs, with a strong focus on data quality, lineage, and schema evolution. • Lead Technical Design for Clients: Serve as the technical lead for complex client implementations, defining highly available, fault‑tolerant architectures across multi‑account cloud environments. • Translate Business Needs into Architecture: Convert complex business and regulatory requirements into scalable technical designs, detailed specifications, and reusable engineering patterns. • Set Engineering Standards: Establish and champion best practices across CI/CD, code quality, testing, orchestration, monitoring, logging, and observability for data platforms. • Ensure Security & Compliance: Design and implement security‑first data solutions, including RBAC, encryption, PHI handling, auditability, and alignment with HIPAA and SOC 2 requirements. • Optimize Performance & Cost: Profile and tune compute workloads, cluster configurations, partitioning strategies, indexing, and caching across Databricks and Snowflake environments. • Provide Technical Mentorship: Mentor senior and junior engineers, conduct design and code reviews, and raise the overall technical bar across teams. • Produce Technical Artifacts: Create clear documentation, including architecture diagrams, runbooks, and operational standards that support scalable delivery.
Strategic planning, enterprise architecture, and governance framework solutions for Health and Human Services
• Design information architecture to support an operational data store for data exchange across the Medicaid enterprise • Design and engineer 100% AWS cloud-native application components • Develop solution prototypes to demonstrate suitability and interoperability of chosen components, and to establish patterns for adoption by implementation team • Review data architectures to determine effectiveness, efficiency, and alignment with enterprise objectives • Develop comprehensive implementation and remediation strategies for data architecture non-compliance • Develop an architectural strategy for metadata management, including tooling and metadata governance • Manage metadata models that support data quality and mastering processes • Develop and maintain Conceptual, Logical, and Physical data models at the enterprise level and for specific data domains within Medicaid (Provider, Member, Claim, Reference) • Review data models with business owners and obtain approval from the data governance committee • Define, and maintain, business rules for data elements in conjunction with business owners and the data governance committee • Research emerging technologies, data modelling methods, and information management systems • Perform data mapping between the canonical models and data formats (both input and output) such as X12 EDI, FHIR, and other structured JSON, XML, or proprietary formats • Support database administrators, network designers and IT personnel on designing and managing the organization's data infrastructure and overall data strategy • Participate in Data Governance Committee meetings, representing the architecture team • Collaborate with internal and external personnel, including solution architects, software developers, database administrators, design analysts and information modelling experts to determine project capabilities, requirements, and timelines
Dragos is a computer and network security company specializing in industrial cybersecurity, incident response, threat intelligence, and security software. Past
At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake. Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place. About the Role You will be joining the Data Engineering Community that specializes in data pipeline design within a matrix style organization. This community serves as the connective tissue for aligning data strategy, sharing best practices, and accelerating innovation across diverse product-focused initiatives. You will be working cross-functionally to create analytics and pipelines to discover IOCs on xOT assets within networks. Responsibilities As a Principal Data Engineer within the Data Engineering Community, you will: Lead cross-functional efforts to re-architect or modernize core data systems. Create sustainable data contracts that address data governance requirements. Enable scalable, secure, and reliable data pipelines that support both cloud and on-prem environments. Implement real-time data processing solutions for configuration and asset communication pipelines. Partners with leadership to align team efforts to broaden company data strategy. Collaborate with product engineering teams to deliver data solutions that enhance customer-facing products. Establish and contribute to shared tooling for observability, lineage tracking, and configuration validation. Minimum Qualifications - 10+ years of data engineering experience - Cybersecurity experience - Architecture expertise creating scalable systems, designing efficient data storage and processing systems. - Expertise in data modeling including incremental models, dimensional models, network topologies and graph structures. - Cross-functional communication skills. - Skilled in implementing data observability frameworks, designing robust data contracts, and optimizing data structures for performance and scalability. - Software development skills in Rust, Go, JVM-family, Python, and/or Node.js languages. - Experience manipulating, processing, and extracting value from medium-to-large scale datasets, especially relevant if cybersecurity or industrial data. - Knowledge of integrating cloud and on-premises technologies in industrial environments, with deployments on Kubernetes and Docker. - Experience with message queues, stream processing on deployable infrastructure. - Detailed domain familiarity and prior experience in at least one data-heavy field / product market segment, especially relevant if knowledgeable in cybersecurity threat detections, threat intelligence, or ICS/OT operations. Even if you don’t think you meet all of these qualifications, we encourage you to apply. We are always on the lookout for good data engineers and even if this role isn’t a good fit, we may have other opportunities for you to explore. Compensation: - Salary: 225,000.00 - Competitive Equity Package - Comprehensive Benefits Plan #LI-JF1 #LI-REMOTE #LI-NH1 #LI-REMOTE Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.
Dragos is a computer and network security company specializing in industrial cybersecurity, incident response, threat intelligence, and security software. Past
At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake. Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place. About the Role You will be joining the Data Engineering Community that specializes in data pipeline and structure design within a matrix style organization. This community serves as the connective tissue for aligning data strategy, sharing best practices, and accelerating innovation across diverse product-focused initiatives. Responsibilities As a Staff Data Engineer within the Data Engineering Community, you will: Create sustainable data contracts that address data governance requirements. Model complex data sources into performant analytics. Create and manage a data transformation layer that can become a core part of our analytic process. Collaborate with product engineering teams to deliver data solutions that enhance customer-facing products. Establish and contribute to shared tooling for observability, lineage tracking, and configuration validation. Minimum Qualifications - 7+ years of data engineering experience. - Cybersecurity experience - Experience dimensional modeling and working with incremental data models. - Skilled in implementing data observability frameworks, designing robust data contracts, and optimizing data structures for performance and scalability. - Software development skills in Go, JVM-family, Python, and/or Node.js languages with cloud-native architectures. - Experience manipulating, processing, and extracting value from medium-to-large scale datasets, especially relevant if cybersecurity or industrial data. - Knowledge of integrating cloud and on-premises technologies in industrial environments, with deployments on Kubernetes and Docker. - Experience with message queuing, stream processing on deployable infrastructure. - Detailed domain familiarity and prior experience in at least one data-heavy field / product market segment, especially relevant if knowledgeable in cybersecurity threat detections, threat intelligence, or ICS/OT operations. Even if you don’t think you meet all of these qualifications, we encourage you to apply. We are always on the lookout for good data engineers and even if this role isn’t a good fit, we may have other opportunities for you to explore. Compensation: - Salary: 192,000.00 - Competitive Equity Package - Comprehensive Benefits Plan #LI-JF1 #LI-REMOTE #LI-NH1 #LI-REMOTE Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.
We are an Alphabet company bringing the promise of precision health to everyone, every day.
• Architect FHIR-compliant data models • Design and operationalize data harmonization strategies • Establish validation frameworks to ensure data accuracy • Collaborate with cross-functional teams on analytics and research initiatives • Develop documentation for data design requirements
Role Description This is a remote position. We are seeking an experienced Intermediate Data Engineer to support the Digital Regulatory Assurance System (DRAS), a strategic initiative focused on modernising environmental and natural resource regulatory processes. The successful candidate will design, build, and maintain scalable Azure-based data solutions that enable analytics, reporting, regulatory compliance, and future AI initiatives. Qualifications - Post-secondary degree, diploma, or certificate in Computer Science or a related field. - 5+ years of hands-on experience with Python and SQL for data engineering. - 4+ years of experience using GitHub/Git for version control and collaborative development. - 3+ years of experience with: - Azure Infrastructure and Services - Azure Databricks - Azure Data Factory - Azure Synapse Analytics - Building scalable data pipelines - Designing analytics-ready data platforms - 2+ years of experience in data governance, metadata management, and security within Azure Databricks environments. - 1+ year of experience using AI-driven tools for code generation, automation, or development productivity. Requirements - Experience with Microsoft SQL Server. - Experience building scalable ETL pipelines. - Experience with Microsoft Fabric. - Experience designing and integrating RESTful APIs. - Experience working with ServiceNow data integrations. - Experience with Azure-based cloud environments in the Government of Alberta. - Experience with message queuing technologies. - Strong understanding of data warehousing, data modelling, and enterprise analytics.
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Python, AWS, SQL, Cloud, Data Engineering, Azure
