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Trilon Group provides smart and sustainable infrastructure solutions across transportation, water, energy, environment, and community sectors. The firm offers a
Data Engineer Department: IT Job Description: Employment Type: Full Time Location: Remote- USA Compensation: $116,000 - $155,000 / year Description Trilon is building a supercharged, technology-enabled future for our people and partners. The Data Engineer plays a key role in that mission by building and maintaining the data platform that powers Trilon's enterprise analytics, automation, and AI capabilities. Reporting to the Vice President, Data & DevOps, this role is responsible for designing, developing, and maintaining scalable data integrations and transformations in Azure and Microsoft Fabric. The Data Engineer ensures that Trilon's data platform delivers reliable, high-quality, and well-structured data to support business intelligence, operations, and innovation. This role serves as the primary custodian of Trilon's integrated data model and is instrumental in developing a unified, extensible architecture that scales with continued acquisitions. The Data Engineer designs and builds secure Power BI semantic models for consumption by analysts and decision-makers, ensuring consistent and governed access to enterprise data. This role also partners closely with the AI and Innovation vTeam to prepare data for analytics, machine learning, and retrieval-augmented generation (RAG) applications. Key Responsibilities Data Platform Engineering and Maintenance - Serve as the primary owner and technical steward of the Trilon enterprise data platform - Design, develop, and maintain data pipelines and workflows using Azure Data Factory, Synapse, and Microsoft Fabric - Build and manage data transformations, orchestration, and automation across structured, semi-structured, and unstructured data sources - Ensure scalability, reliability, and performance of the data platform as Trilon continues to grow through acquisition - Implement monitoring and alerting to proactively detect and resolve pipeline or data quality issues Data Integration and Modeling - Develop and maintain integrations between Trilon's enterprise systems, cloud services, and acquired partner environments - Design and maintain a unified, scalable data model that harmonizes data across business systems - Build secure, governed, and high-performance Power BI semantic models optimized for analytics and self-service reporting - Collaborate with business analysts and data consumers to ensure data models support enterprise reporting needs and KPIs - Partner with cybersecurity and infrastructure teams to ensure data models and access patterns meet compliance and governance standards Data Quality and Governance - Implement validation and quality checks to ensure accuracy, completeness, and timeliness of enterprise data sets - Maintain metadata, lineage, and documentation to promote transparency and reusability - Define and enforce data quality and consistency standards across all integrated sources - Collaborate with the Technology Asset Manager and Service Platform Manager to align system integrations and data governance - Support data cataloging, discovery, and classification initiatives within Microsoft Purview or equivalent tools Automation, Optimization, and Resilience - Develop automated frameworks for ingestion, transformation, and validation using Azure-native tools and pipelines - Implement DevOps principles for data workflows including version control, testing, and deployment automation - Optimize pipeline performance, resource utilization, and data freshness - Build resilience and fault tolerance into data operations to ensure reliability and recovery - Create reusable components and templates to streamline integration of new data sources and partner systems AI and Innovation Enablement - Collaborate with the AI and Innovation vTeam to prepare and structure data for AI, ML, and RAG-based applications - Develop and maintain data pipelines that support model training, evaluation, and fine-tuning - Curate and transform unstructured data for retrieval, embedding, and vectorization within AI applications - Ensure data readiness for generative AI tools, chat interfaces, and knowledge retrieval systems - Stay informed of emerging AI data engineering trends and Microsoft Fabric AI integrations Collaboration and Cross-Domain Partnership - Partner with application and infrastructure teams to ensure reliable and secure data exchange across systems - Collaborate with business stakeholders and analysts to understand reporting needs and deliver usable data models - Support integration engineers in onboarding new firms and ensuring their data aligns with Trilon's enterprise model - Work closely with cybersecurity and compliance teams to enforce data protection, retention, and access policies - Provide documentation, architecture diagrams, and operational standards for the data platform and pipelines Skills, Knowledge and Expertise - 5 or more years of experience in data engineering, data integration, or data platform development - Strong hands-on experience with Azure Data Factory, Azure Synapse, Microsoft Fabric, and related Azure data services - Proficiency in SQL, DAX, Power Query, and data modeling for Power BI - Experience designing and maintaining Power BI semantic models, datasets, and row-level security configurations - Familiarity with data governance, cataloging, and lineage management in tools like Microsoft Purview - Experience building and optimizing cloud data pipelines with structured, semi-structured, and unstructured data - Understanding of data preparation for AI and machine learning applications, including RAG architectures - Exposure to engineering and geospatial data such as CAD, BIM, and GIS - Strong analytical and problem-solving skills with a focus on scalability and performance - Excellent collaboration and communication skills across technical and business audiences - Bachelor's degree in Computer Science, Data Engineering, or related field preferred - Microsoft certifications such as Azure Data Engineer Associate or Fabric Analytics Engineer Associate are a plus - May require occasional travel to Trilon offices or partner locations for integration or collaboration activities About Trilon Trilon was formed with the vision of building the next Top 20 infrastructure consulting firm in North America by bringing together some of the nation's best infrastructure consulting firms, focused on delivering practical and sustainable infrastructure solutions. Trilon is backed by Alpine Investors, a PeopleFirst Private Equity Firm. Trilon currently comprises 5,500+ staff across the US. For more information, visit www.trilon.com. Pay Transparency The base salary range for this role is indicated in the posting. This range reflects the company's good faith estimate of the compensation for this position at the time of posting. Final compensation will be determined based on factors such as experience, skills, qualifications, internal equity, and geographic location.
Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients. Founded in 2009, we are smaller, faster, and more senior by design, with teams averaging 15+ years of experience.
Role Description We’re looking for a Staff Data Engineer to join a multi-disciplinary engineering team building modern, enterprise-grade data platforms. This role is ideal for an experienced engineer who can define data strategy, own platform decisions end-to-end, and contribute to technical leadership across the team. - Design scalable data lakes, warehouses, and pipelines. - Define governance and quality standards. - Drive data platform modernization across real, in-flight work where performance, reliability, and security are critical. - Mentor more junior engineers. - Partner with leadership on data strategy. - Bring an AI-forward mindset. What You’ll Do Craft & Delivery - Define data architecture and platform strategy, leading design across pipelines, warehouses, and data lakes. - Build and optimize scalable data pipelines supporting batch and real-time processing. - Define and enforce data governance, quality standards, and compliance frameworks across the platform. - Build monitoring, logging, and alerting for data pipelines and services, and contribute to CI/CD workflows for data deployment and automation. - Drive data platform modernization, optimizing for performance, cost, and scalability. - Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants. - Design and implement data contracts and event flows in collaboration with backend, platform, and engineering teams. - Lead the design and implementation of data pipelines for production AI/ML systems. - Integrate data services with APIs, middleware, and third-party systems to support end-to-end data consumption. Collaboration & Communication - Partner with leadership on data strategy, translating technical depth into decisions others can act on. - Collaborate closely with engineering, analytics, AI, and product teams to align data platforms with broader goals. - Advocate for data quality, governance, and platform best practices across teams and engagements. Leadership & Influence - Establish data engineering standards that lift the quality and consistency of work across the team. - Mentor junior and mid-level engineers, helping them grow their craft, confidence, and impact. - Make high-stakes architectural decisions with clear ownership and consideration of long-term tradeoffs. Qualifications - 7+ years of professional data engineering experience, with experience leading complex data platform initiatives. - Strong system architecture background with expertise in distributed data systems. - Expert proficiency in Python, Scala, and SQL. - Deep expertise with cloud-native data platforms and enterprise data warehousing. - Strong expertise in data pipeline orchestration and processing. - Strong experience with streaming platforms and real-time data processing (e.g., Kafka, Kinesis, Pub/Sub). - Strong data modeling expertise and experience with data transformation. - Strong experience with data quality, governance, and compliance frameworks. - Strong experience with container orchestration and CI/CD for data systems. - Strong experience building data pipelines for production AI/ML systems. - Demonstrated leadership and technical mentoring experience across a team or organization. - Strong stakeholder communication skills, with the ability to translate technical depth across audiences. - Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor. - Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment. - Experience with data mesh or data fabric concepts, lakehouse architectures, or governance framework implementation is a plus. Helpful Extras and Unique Skills - Experience with handling and modeling data in the healthcare industry is a plus. - AWS certifications, like Certified Data Engineer – Associate, strongly preferred. Benefits - A doer who sees something broken and fixes it. - A fast learner who embraces the changing AI landscape. - Direct in a way that improves work quality. - Obsessed with craft and detail. - Built for ownership and accountability. - All in for client success. - Resourceful in tight constraints. - Glad to collaborate with passionate teammates.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.
Role Description We’re seeking a Mid-Level Data Engineer/Analyst to independently design, build, and optimize data pipelines and analytics solutions that power business intelligence and AI/ML initiatives. In this role, you will own key data workstreams end to end, build production-grade transformation layers using dbt and Spark, manage data infrastructure on Snowflake and Databricks, and collaborate with analysts, data scientists, and product teams to deliver reliable, well-governed, and high-quality data products. You will also contribute to the maturity of our DataOps and data observability practices. - Design, build, and maintain production-grade ETL/ELT pipelines using dbt, Apache Spark (PySpark), Airflow, Dagster, or Prefect. - Develop and optimize data models on Snowflake, Databricks, BigQuery, or Redshift following dimensional modeling, data vault, or One Big Table patterns. - Implement and manage data ingestion from diverse sources including databases, REST/GraphQL APIs, event streams (Kafka, Kinesis), SaaS platforms, and flat files using Fivetran, Airbyte, or custom connectors. - Build and maintain semantic/metrics layers and curated data products for analytics, reporting, and self-service consumption. - Implement data quality, testing, and observability frameworks using dbt tests, Great Expectations, Soda, Monte Carlo, or Datafold. - Create advanced dashboards, reports, and analytical visualizations using Tableau, Looker, Power BI, or Sigma Computing. - Optimize query performance, pipeline efficiency, and cloud data platform costs across Snowflake, Databricks, or BigQuery. - Collaborate with data scientists and ML engineers to prepare and serve feature datasets for machine learning models. - Implement DataOps practices including CI/CD for data pipelines, version-controlled transformations, and automated testing. - Write production-quality Python and SQL code with proper testing, documentation, and error handling. - Support data governance initiatives including cataloging, lineage tracking, access controls, and PII management using tools like Alation, Atlan, DataHub, or Unity Catalog. Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. - 3–5 years of professional experience in data engineering, analytics engineering, or a closely related role with production delivery. - Strong proficiency in SQL and experience writing complex transformations, window functions, CTEs, and performance-tuned queries. - Hands-on experience with at least one modern data platform: Snowflake (strongly preferred), Databricks, BigQuery, or Redshift. - Experience with dbt (data build tool) for data transformation, testing, and documentation in production environments. - Working knowledge of Python (Pandas, PySpark, or Polars) for data processing and pipeline development. - Experience with workflow orchestration tools: Airflow, Dagster, Prefect, or cloud-native equivalents (AWS Step Functions, Azure Data Factory). - Familiarity with data ingestion tools and patterns: Fivetran, Airbyte, CDC (Debezium), or streaming ingestion (Kafka, Kinesis). - Experience with data visualization and BI tools: Tableau, Looker, Power BI, or Sigma. - Understanding of data modeling methodologies (Kimball, Data Vault, OBT) and data warehousing best practices. - Familiarity with version control (Git), CI/CD for data, and Agile development workflows. Preferred Qualifications - Snowflake SnowPro Core, Databricks Data Engineer Associate, or AWS Data Analytics Specialty certification. - Experience with Apache Spark and Databricks for large-scale data processing and lakehouse architectures. - Familiarity with data cataloging and governance tools: Alation, Atlan, DataHub, Collibra, or Databricks Unity Catalog. - Experience with data observability platforms: Monte Carlo, Datafold, Soda, or Elementary. - Exposure to streaming data pipelines using Kafka, Spark Structured Streaming, Flink, or Kinesis. - Experience with metrics/semantic layers: dbt Semantic Layer, Cube, or Looker Modeling Language (LookML). - Knowledge of cloud data infrastructure: AWS (S3, Glue, Athena, Redshift, Lake Formation), Azure (ADLS, Synapse, Data Factory), or GCP (GCS, Dataflow, BigQuery). Benefits - Unlimited PTO. - Very generous parental leave, much above industry standards. - Entrepreneurial culture where pushing limits and taking risks is everyday business. - Open communication with management and company leadership. - Small, dynamic teams = massive impact. - Medical, Dental and Vision coverage for employees. - Access to Disability & Life insurance. - Mental health and wellbeing support. - Annual bonus program. - Employer Stock Purchase Program (ESPP). - Yearly Team building experiences. - Mentorship and sponsorship opportunities. - Manager resources and support.
Role Description We are seeking a dependable and detail-oriented Remote Data Entry Assistant to support daily administrative and data management operations. The ideal candidate will accurately enter, update, and verify information across company systems while maintaining confidentiality and meeting productivity and accuracy standards in a remote work environment. - Enter, update, and maintain data in company databases, spreadsheets, and CRM systems. - Verify information for accuracy and correct errors or inconsistencies. - Organize and maintain electronic records and digital files. - Perform routine data quality checks and generate basic reports as requested. - Assist with document processing, file management, and other administrative tasks. - Maintain confidentiality of sensitive customer and company information. - Meet daily productivity and accuracy goals. - Communicate with team members to resolve data discrepancies and support workflow improvements. Qualifications - High school diploma or equivalent required; Associate's degree preferred. - 0–2 years of experience in data entry, administrative support, or clerical work preferred. - Typing speed of 45+ WPM with strong accuracy. - Proficiency in Microsoft Office (especially Excel), Google Workspace, and basic database systems. - Strong attention to detail, organization, and time management skills. - Ability to work independently in a remote environment. - Reliable high-speed internet connection and a dedicated home office. Benefits - Competitive hourly pay - Health, dental, and vision insurance - 401(k) with company match - Paid time off and company holidays - Flexible remote work schedule - Paid training and professional development - Home office equipment stipend - Employee assistance program (EAP) - Performance-based bonuses - Career advancement opportunities
Virtual care provider on a mission to positively transform the lives of individuals living with chronic conditions
• Lead the design, development, and implementation of enterprise data architecture for the new platform • Architect scalable data platforms supporting daily operations, clinical management, reporting, and analytics • Leverage AI technology to design the system, develop the system, and maximize efficiency of operations • Design and maintain enterprise data models, including conceptual, logical, and physical data architectures • Define and implement data integration patterns across Microsoft Dynamics, EHR/EMR systems, claims systems, and third-party applications • Design and oversee ETL/ELT processes to ingest, transform, validate, and distribute data across enterprise systems • Establish data governance standards, metadata management practices, data quality frameworks, and master data management strategies • Collaborate with Engineering teams to design modern cloud-based data solutions leveraging Azure data services • Architect data lake, data warehouse, and data mart solutions to support reporting and advanced analytics needs • Ensure solutions comply with HIPAA, HITRUST, privacy, security, commercial, and regulatory requirements • Partner with business stakeholders to translate strategic objectives into scalable data solutions • Other duties as assigned
Vultr is on a mission to make high-performance cloud computing easy to use, affordable, and locally accessible.
• Design and implement the canonical data model for Vultr’s control plane ERP transformation: product catalog, chart of accounts, financial transactions, cost centers • Build and maintain the internal APIs and event streams that Finance, Analytics, and downstream systems consume • Refactor existing administer code toward clean domain boundaries (no more conflated orders/ledger/report tables) • Implement data upgrade/migration paths from legacy schemas without breaking production • Write the integration layer between administer and Vultr's existing billing, provisioning, and reporting systems • Establish data validation and integrity checks across the financial data layer • Collaborate with the Product Manager to translate finance domain requirements into durable schema designs • Document architectural decisions and data model contracts for downstream consumers
• Define and own the strategic architecture of Foodsmart's data platform • Lead the design and implementation of next-generation data pipelines • Establish company-wide standards for data quality, governance, security, and compliance • Act as a cross-functional technical leader, partnering with engineering, product, data science, and business stakeholders • Identify systemic bottlenecks and drive platform-wide improvements • Mentor and level up engineers; influence hiring decisions and data platform strategy • Serve as an internal authority on data engineering best practices
A health management technology company, Privia Health is a national practice led by physicians. The company was founded in 2007 to provide physician groups with resources dedicated
Role Description The Full Stack Engineer is a highly skilled developer equally at home in Ruby and SQL. Our team develops and maintains a stable of Rails applications that power our core patient- and provider-facing digital products. You will act as the data backbone supporting real-time and operational products, with examples as: - Patient automated actions - MyPrivia patient portal - Privia Insights (embedded inside athenaOne) - Online scheduling - Communication orchestration layers We are looking for an engineer who actively integrates AI-assisted coding tools to accelerate development, optimization, and testing. You must have experience translating complex business requirements into scalable, secure, cloud-native data architectures while partnering with a distributed team of engineers. Our team is currently 7 developers. We all work remotely, and have for more than 10 years. Our team is highly collaborative, we succeed and fail together, not as individuals. We maintain a stable of Rails/React applications ranging from microservices to majestic monoliths. We have a culture of mentorship and knowledge sharing. We work using the Scrum process, in two week sprints. We proudly have a trans-inclusive and family friendly health plan, plus a lot of other great benefits. Primary Job Duties: - Product-Driven Engineering: Design, build, and maintain high-performing rails and javascript applications that power core application features and support our mobile applications. - Data Modelling and Development: Provide hands-on development of data models, data load pipelines and SQL scripts in MySQL and Snowflake. - AI-Augmented Development: Integrate AI-assisted programming tools (e.g., Gemini) into daily development workflows to optimize SQL queries, accelerate application development, and build robust automated test suites. - Data Integrity & Quality Assurance: Build and maintain unit and integration tests for the applications and databases we support. - Agile Collaboration: Collaborate directly with product owners and business analysts to plan and define data requirements, actively participating in and contributing to Scrum/Agile ceremonies. Qualifications - 4+ years of experience with Ruby On Rails - 5+ years of experience with SQL database development, ideally in a cloud environment such as Google Cloud or Snowflake - Strong hands-on experience utilizing public cloud services (AWS, Azure or GCP) alongside modern data platforms like Snowflake. - Experience using AI development assistants to write, optimize, and debug code. - Proven experience delivering value within an Agile/Scrum team structure. Requirements - Experience engineering data workflows specifically for patient engagement, digital health portals, or automated scheduling products. - Deep, practical knowledge of healthcare data ecosystems (claims data, clinical EHR workflows, patient scheduling patterns) and strict compliance with HIPAA rules and regulations. - Experience with modern data transformation orchestration tools (such as dbt, Airflow, or Prefect). - Prompt engineering skills or experience fine-tuning AI tools for development workflows. Benefits - Trans-inclusive and family friendly health plan - Annual bonus targeted at 15% - Expense reimbursement for remote work-related costs Additional Information All your information will be kept confidential according to EEO guidelines. The salary range for this role is $110,000.00 to $130,000.00 in base pay and exclusive of any bonuses or benefits (medical, dental, vision, life, and pet insurance, 401K, paid time off, and other wellness programs). The base pay offered will be determined based on relevant factors such as experience, education, and geographic location. In order to successfully work remotely, supporting our patients and providers, we require a minimum of 5 MBPS for Download Speed and 3 MBPS for the Upload Speed. This should be acquired prior to the start of your employment. The best measure of your internet speed is to use online speed tests like https://www.speedtest.net/ . Employees who regularly work from home offices are eligible for expense reimbursement to offset this cost. Privia Health is committed to creating and fostering a work environment that allows and encourages you to bring your whole self to work. We understand that healthcare is local and we are better when our people are a reflection of the communities that we serve. Our goal is to encourage people to pursue all opportunities regardless of their age, color, national origin, physical or mental (dis)ability, race, religion, gender, sex, gender identity and/or expression, marital status, veteran status, or any other characteristic protected by federal, state or local law.
At BILL, we believe in empowering the businesses that drive our economy. By replacing outdated financial processes with innovative tools, we help businesses—from startups to established brands—make smarter decisions and gain control of their operations. We value purpose, drive, and curiosity—and we thrive in a fast-paced, ever-changing environment. BILL builds high performing teams and we seek to hire the best talent for every role.
Role Description The Data Platform team builds and operates BILL’s core data infrastructure, providing the end-to-end foundation that collects, stores, processes, governs, and serves data so every team at BILL can use it. We own the full data stack: inbound and outbound data lake, real-time streaming pipelines, batch processing, and data access layers including a Starburst query engine, Databricks Feature Store, Neo4j Knowledge Graph, and OpenSearch. Some capabilities require real-time access with strict low-latency SLAs. Our charter is to simplify the data landscape and power AI at BILL. To achieve this, we focus on building scalable platform capabilities rather than creating one-off pipelines or analytics reports. Engineers here work at the systems level: designing architectures, incubating new capabilities, setting standards, and enabling the rest of BILL to self-serve. The team sits within the CTO organization. Responsibilities - Operate at the architectural level, driving platform-wide technical decisions and mentoring the team. - Own and evolve critical infrastructure across the full data lifecycle, spanning ingest, store, enrich, query, and serve. - Architect and own critical data platform capabilities end-to-end, from inbound ingestion through data lake storage to downstream serving, including the feature store, query engine, knowledge graph, and search. - Define technical direction for the team’s most complex, cross-cutting problems, such as streaming versus batch trade-offs, schema contracts, data access patterns, and real-time serving architectures. - Drive design and delivery of new capabilities from inception to GA, including reference implementations, SLAs, and clear ownership handoff models. - Establish and maintain architectural standards and engineering patterns adopted across the organization. - Lead multi-phase technical migrations at enterprise scale, including compute platform upgrades, warehouse-to-lake migrations, and infrastructure modernization. - Partner with engineering teams across BILL, such as ML/AI, Risk, Payments, and Analytics, to translate diverse data needs into durable platform solutions. - Mentor senior and staff engineers, actively shaping the technical culture and engineering quality bar of the team. - Own and continuously improve critical production systems with a focus on reliability, cost efficiency, and a self-serve developer experience. Qualifications - Bachelors degree in Computer Science, Engineering, Mathematics, or equivalent work experience. - 8+ years of experience in data engineering, distributed systems, or software engineering with a heavy focus on data infrastructure. - 5+ years of experience specifically on data platform, data infrastructure, or data systems teams, rather than purely analytics or BI roles. - Expertise in distributed systems design for data workloads, including a deep understanding of streaming, batch, and real-time serving trade-offs. - Hands-on experience with event streaming platforms (such as Kafka, Flink, Spark Streaming, or equivalent) and CDC-based ingestion patterns. - Strong proficiency with batch processing stacks (such as Airflow, dbt, Spark/Glue, or equivalent). - Experience with modern open table formats and data lake architectures, including Apache Iceberg, Delta Lake, or equivalent frameworks. - Familiarity with data access and serving layers, including query engines (Trino/Starburst, Presto), feature stores, vector stores, or graph databases. - Expert-level SQL and strong Python skills, backed by solid software engineering fundamentals such as CI/CD, testing, and observability. - Demonstrated experience architecting and operating large-scale, production-grade data platforms. - A proven track record operating as a technical lead, with the ability to drive ambiguous, high-impact projects from first principles to production. - The ability to define technical standards that hold across organizational boundaries rather than just within a single team. Desired Qualifications - 3+ years of experience in financial services, fintech, or SaaS companies. - Experience building self-serve data platforms or developer-facing infrastructure tooling. - Experience working in fintech, financial data, or highly regulated data environments. Benefits - 100% paid employee health, dental, and vision plans (choose HMO, PPO, or HDHP). - HSA & FSA accounts. - Life Insurance, Long & Short-term disability coverage. - Employee Assistance Program (EAP). - 11+ Observed holidays and wellness days and flexible time off. - Employee Stock Purchase Program with employee discounts. - Wellness & Fitness initiatives. - Employee recognition and referral programs. - And much more.
• Design and deploy high-performance, distributed web scrapers using Python and Scrapy • Utilize Browser Scripting tools to navigate, interact with, and extract data from websites • Deploy, scale, and manage scraping workloads on Kubernetes • Define strict JSON Schemas and leverage Pydantic for data validation • Build and optimize search and storage pipelines using Elasticsearch • Architect robust pipeline workflows to manage the end-to-end data lifecycle • Manage complex proxy rotation and session handling to maintain high success rates
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SQL, Python, AI, Azure, AI/ML, Observability/Monitoring
