Top Data & Analytics Jobs

The Data QA Engineer is responsible for ensuring data quality through automated testing frameworks, SQL queries, and collaboration with analytics teams.

This role offers training for aspiring Data Engineers, focusing on technology of choice, interview preparation, and skill enhancement with guidance on OPT STEM extension.

As a Snowflake Data Engineer, you will design and maintain scalable data pipelines, optimize SQL transformations, and support analytics platforms, collaborating with stakeholders.

Lead design and implementation of enterprise-scale data architectures, pipelines, and integration frameworks supporting ontologies, knowledge graphs, and Semantic Web technologies. Build and optimize ETL/ELT processes for structured and unstructured data, enable cloud/containerized deployments, ensure data quality, lineage, governance, and support AI/ML initiatives. Provide technical leadership, documentation, automated monitoring, and mentorship to Government stakeholders and project teams.

Own and maintain Center of Excellence network reporting and health metrics. Build recurring and ad hoc dashboards using Databricks, Python, and SQL. Conduct network adequacy and coverage analysis, validate and distribute reports, surface risks and trends, support client meetings, and produce executive-ready summaries while documenting processes and standards.

Design, build, and optimize T-SQL queries, stored procedures, and SSIS ETL packages. Provision and maintain AWS RDS instances, monitor performance, apply security best practices, migrate legacy packages, support BI/reporting teams, and participate in code reviews and data architecture.

Design, build, and scale enterprise Power BI reporting and centralized semantic models. Develop advanced DAX and Power Query solutions, optimize report performance, implement RLS and governance, partner with business and data engineering to enable self-service analytics and standardized metrics, and deliver executive-ready dashboards supporting insurance business decisions.

Lead analytics strategy for product, CRM, and acquisition; run and interpret A/B and multivariate tests; enhance web analytics and data models; build and QA Tableau dashboards and data pipelines; mentor one analyst; present executive-ready insights and resolve cross-platform data integrity issues to drive growth.

Design, build, and maintain scalable data ingestion pipelines into BigQuery; replace legacy ETL/ELT; implement orchestration (Airflow/Dagster/Prefect); support DBT and CI/CD; tune BigQuery performance; set up monitoring/alerting; maintain documentation and data governance.

Lead data cleansing, validation, and certification for ERP data conversion. Produce auditable validation results, triage and resolve data issues, document evidence for certification, and collaborate with cross-functional teams to ensure data quality throughout the conversion lifecycle.