Top Remote Data & Analytics Jobs

Leads the design, development, and operation of Astrana’s enterprise data platform. Builds scalable Databricks, Spark, PySpark, SQL, and Delta Lake pipelines; integrates healthcare data; develops unified data models and APIs; supports Lakebase and PostgreSQL applications; and implements governance, data quality, monitoring, CI/CD, automation, and performance optimization. The role also handles incidents, disaster recovery coordination, engineering standards, code reviews, and mentoring across internal and vendor teams.

Build and deploy scalable data pipelines and platforms that organize structured and unstructured data for mission-driven client projects. Collaborate with analysts, developers, data engineers, and data consumers in an agile environment. Support data assessment, exploration, examination, platform design, development, and maintenance. The role requires Palantir Foundry, Python, CI/CD, SQL, TS/SCI clearance, and travel to OCONUS locations up to 25% of the time.

Develop and maintain Python scripts and automated workflows for NLM metadata management. Integrate Alma, OCLC, and other systems through APIs and batch exchanges; process, transform, validate, reconcile, and analyze bibliographic and authority metadata in formats including MARC, XML, JSON, and CSV. Implement logging, exception handling, reporting, and documentation while supporting workflow testing, systems integration, and automation improvements.

Conducts customer experience research and analysis through stakeholder interviews, surveys, journey mapping, and performance data review. Manages the survey request process, programs and configures surveys in Qualtrics, establishes notifications, analyzes survey insights, and develops recommendations, presentations, and communications for leadership. Supports customer-focused product, service, and operational improvements in a federal consulting environment.

Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and compliant data delivery. Partner with governance, privacy, architecture, modeling, and platform teams to ensure reliable, traceable, protected data products. Monitor operational performance, automate deployment and validation, and resolve pipeline and data reliability issues across complex enterprise environments.

The AVP, Data Engineer will design and build data ingestion, transformation, and replication pipelines using SQL, Python, dbt, and Dagster. Responsibilities include translating requirements into technical designs, developing data products, debugging production issues, supporting testing, and improving data engineering practices. The role also involves data modeling, mentoring junior engineers, conducting code reviews, and providing technical leadership while remaining hands-on. Experience with modern data platforms, workflow orchestration, cloud ecosystems, and insurance or financial services is preferred.

Leads enterprise data architecture for a federal transportation agency, including data modeling, data warehouses, data marts, database design, ETL/ELT integration, governance, and cloud modernization. The role architects AWS-based solutions, supports migrations to Databricks and data lakes, integrates disparate systems, and provides technical leadership to stakeholders and development teams.

Leads PBM data integration programs involving claims, eligibility, accumulator, and encounter data. Profiles, maps, validates, and reconciles data using advanced SQL; investigates production issues; designs scalable healthcare integrations; coordinates vendors, engineering, testing, UAT, migration, and deployment readiness; and manages timelines, risks, dependencies, and executive reporting. The role also maintains documentation and operational procedures while directing day-to-day integration work.

Analyze customer journeys, churn, acquisition, activation, retention, attribution, experimentation, and conversion. Develop advanced models and actionable strategy recommendations for B2C Marketing. Partner with stakeholders and data engineering to define metrics, improve data quality and governance, and build scalable dashboards using modern analytics and visualization tools. Independently manage multiple complex projects and identify opportunities that support business objectives.

Analyzes structured and unstructured data to identify and resolve quality issues, develop data quality standards, create automated reports and dashboards, and support CMS fraud, waste, and abuse initiatives. The role performs statistical analysis, collaborates with data and reporting teams, presents findings to stakeholders, participates in Agile ceremonies, mentors junior analysts, and provides technical leadership across data quality projects.