Top Data & Analytics Jobs in NYC, NY

Analyze customer journey interactions and connect them to business outcomes using clickstream data. Develop measurement frameworks, synthesize behavioral insights, and collaborate cross-functionally to optimize digital experiences.

Lead a small second-line team providing independent oversight of enterprise data governance. Assess governance frameworks, data ownership, quality controls, risk identification, and regulatory alignment. Deliver actionable insights to senior management, partner with first-line teams to improve governance maturity, and validate controls and issue management practices across the firm.

Design and operate metadata cataloging, lineage harvesting, governance workflows, and data quality for unstructured data. Configure and maintain Atlan/Anomalo/Unity Catalog, build automated checks and prototypes using Python/SQL/Databricks/Streamlit, collaborate with stakeholders, document standards, and drive governance tool adoption.

The Senior Associate will analyze business needs, translate them into technical requirements, and collaborate with teams on enterprise-scale tech solutions, primarily in life insurance operations.

Design, build, and optimize SQL and NoSQL database solutions (PostgreSQL, Elasticsearch, DynamoDB). Develop stored procedures, functions, triggers, and complex queries. Implement CDC and AWS DMS, manage platform via GitHub/CI-CD and Terraform, monitor and tune performance, participate in Level 3 on-call, and collaborate with analysts, architects, and developers to deliver scalable data services.

The Data Governance and Stewardship Lead will develop and implement a data governance framework, ensuring data quality and compliance, and collaborating with business and technology teams.

The Corporate Vice President will design and implement actuarial data architecture, integrating platforms into cloud systems while leading teams and maintaining data governance.

Design and implement data management strategies, creating scalable data solutions, and collaborating with teams to address business challenges and ensure data integrity.

Design and implement data pipelines, manage data with SQL and Python, automate workflows, ensure data integrity, and build scalable data solutions on AWS and Redshift.

Design, build, and maintain scalable dbt transformation pipelines and analytical data products on cloud platforms. Own data product lifecycle from source alignment and modeling to deployment, testing, monitoring, and governance. Implement automated data quality, observability, and metadata practices; develop reusable macros and semantic-layer assets. Collaborate with stakeholders, mentor peers, and promote analytics engineering standards to support reporting, advanced analytics, and AI use cases.