Top Data & Analytics Jobs

Design, build, and maintain scalable data ingestion and ETL pipelines across a growing data lake. Define and enforce data quality standards, SLOs, and validation frameworks. Optimize pipelines for performance and cost, expand monitoring and alerting, and enable stakeholders to self-serve on data infrastructure.

Build and maintain Azure Data Factory ingestion pipelines into Snowflake, implement medallion transformations (Coalesce), write Python orchestration and connectors, apply governance with Atlan, collaborate with AI coding agents, participate in CI/CD with Azure DevOps, handle on-call production support, and document runbooks.

Lead and mentor a data engineering team, define technical vision and strategy, oversee data pipeline design, and collaborate with cross-functional teams.

Lead design and delivery of complex data solutions including data integration, cleaning, transformation, lineage, and migration. Build and document data pipelines, manage ADS and regulatory data lineage, lead testing and cutover for database migrations, create automation and reconciliation scripts, troubleshoot with architects and security teams, and mentor other data engineers.

The Data Engineer will execute data architecture projects, manage data ingestion processes, ensure data quality, and transition data to new systems while collaborating with investment teams.

Design, build, and maintain enterprise analytics solutions and semantic data models using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Deliver scalable reporting datasets, executive dashboards, data quality standards, and CI/CD practices. Lead architecture discussions, mentor engineers, collaborate with stakeholders, and drive analytics strategy to enable data-driven decisions.

Design, build, and maintain enterprise analytics solutions and semantic data models using Microsoft Fabric, Databricks, SQL, Python, and Power BI. Develop reporting datasets, dashboards, and self-service analytics; ensure data quality, performance, CI/CD, and governance; translate business requirements into scalable solutions; provide technical leadership, mentor engineers, and collaborate with architects and stakeholders to align analytics with business objectives.

Design, build, and maintain enterprise analytics solutions, semantic models, and reporting datasets using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Collaborate with product, platform, and business teams to ensure data quality, performance, scalability, and metric governance. Mentor engineers, lead data design discussions, and drive analytics engineering best practices to enable self-service analytics and executive reporting.

Design, build, and maintain enterprise analytics solutions, semantic models, and reporting datasets using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Lead data modeling, data quality, CI/CD, and performance optimization; translate business requirements into scalable analytics; mentor engineers and collaborate with architects and stakeholders to deliver trusted, self-service and executive reporting across the Americas.

Design and implement large-scale GCP-based data platforms and ETL using PySpark/Spark, BigQuery, Dataproc, Composer/Airflow. Process and analyze large datasets, write SQL, collaborate on BI delivery, and work in a mature Agile team.

Build and maintain scalable cloud data pipelines and governance to support analytics across claims, EHR, and real-time patient data. Deploy and operate Snowflake/dbt/AWS-based infrastructure, enable real-time analytics, partner with clinical, product, and engineering teams, and deliver insights that inform care delivery, payer collaboration, and business decisions.

Build and maintain data pipelines and models to provide high-quality data for reporting, BI, and analytics. Work with SQL, dbt, Python, cloud data stores, orchestration tools, and reconciliation systems to support analytics, BI tools, and data warehouse delivery.

Design, build, and maintain ETL/data pipelines and data models (dbt). Work with large datasets across RDBMS and NoSQL, deploy to cloud (AWS preferred), use Python and orchestration tools (Dagster/Prefect/Airflow), support BI/analytics and visualization, and implement data reconciliation for accuracy.

The Data Engineer at Anteriad will design, build, and optimize data pipelines, manage data integration processes, support analytics efforts, and collaborate with stakeholders to deliver scalable data solutions.

Senior individual contributor who designs, builds, and evolves Azure-based enterprise cloud data platform capabilities. Guides architecture, standards, reusable components, automation, security, and enablement for analytics, ingestion, storage, processing, and operationalization while providing hands-on technical leadership and mentorship.

Lead architecture and evolution of Headway's data platform (warehouse, ingestion, orchestration, CI/CD, monitoring, cloud infra). Serve as technical anchor across analytics, product, and ML teams, drive platform roadmaps, set standards, mentor engineers, and own end-to-end infrastructure decisions for scale and performance.

As a Senior Lead Data Engineer, you'll lead a development team, design and implement data solutions using machine learning, distributed systems, and full-stack technologies, while collaborating with Agile teams and ensuring code quality.

Build and optimize high-volume data processing jobs and libraries (Redshift, Athena, Iceberg, Spark, Airflow). Debug and improve query and job performance, and collaborate with data scientists, analysts, and product managers to support analytics and data products.

Lead Data Engineer responsible for designing, building, and supporting scalable cloud data pipelines and platforms. Collaborate across Agile teams to implement distributed computing, data modeling, quality, governance, and real-time streaming solutions using Python, SQL, Snowflake/Databricks, Spark, Kafka, and cloud services. Mentor engineers, participate in code reviews, and drive technical innovation including GenAI tooling.

Lead Data Engineer responsible for designing, building, testing, and supporting scalable data pipelines and cloud-based solutions. Collaborate across Agile teams to optimize data models, ensure data quality and governance, mentor engineers, and apply distributed computing, streaming, and emerging GenAI tooling to deliver personalized marketing and messaging experiences.

Work at the intersection of software engineering and operations to investigate production issues, improve reliability, build automation, enhance observability, and support customers. Develop and maintain C# and SQL Server solutions, reduce manual effort, convert production learnings into lasting improvements, and provide occasional after-hours support.

Own end-to-end consumer data domains: ingest, clean, model, and productionize derived attributes and pipelines. Investigate new data sources, ensure quality and provenance, and partner with engineers, data scientists and product teams to deliver trustworthy data products that power applications, agents, APIs and ML models.

Build and mature data services and analytics in a cloud environment: gather requirements, design data models and pipelines, create Power BI reports, implement data quality checks, support statistical/NLP/AI modeling, and deliver data-driven insights to business stakeholders.

Build, maintain, and optimize cloud-based data pipelines and ETL processes. Collaborate with business stakeholders to design data models and deliver scalable warehousing solutions. Implement data quality checks, monitor performance, document systems, and enable self-service analytics (Power BI). Support migration from legacy systems and drive data engineering best practices across environments.

Maintain and monitor data pipelines that aggregate healthcare claims for the Cost Roll process. Validate and reconcile claim and provider demographic data, troubleshoot data issues, perform data quality checks, and collaborate with stakeholders to ensure reliable downstream financial and clinical systems.