Top Data & Analytics Jobs in NYC, NY

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.

Design, build, and maintain data transformations and models using SQL and dbt to support enterprise reporting and AI initiatives. Implement data quality controls, create analytics datasets, and collaborate with engineering and business teams to deliver trusted dashboards, metrics, and information products.

The Strategic Analytics Lead aligns senior leadership priorities with actionable analysis, integrating diverse data sources to deliver insights and recommendations for decision-making.

The role focuses on competitive intelligence, benchmarking, and translating insights into actionable strategies for the Field Experience team at New York Life.

The Senior Data Engineer will design and execute data management strategies, build cloud solutions, develop data pipelines, and ensure data quality and integrity.

Analyze end-to-end advisor and client journeys to identify friction, root causes, repeat contacts and rework. Translate interaction and operational data into prioritized, actionable insights, partner across Quality, Operations, Training and Leadership to drive improvements, and create executive-ready dashboards and summaries that demonstrate linkage between insights and business outcomes.

The Data Governance Analyst curates metadata, implements governance workflows, supports data quality checks, and drives governance tool adoption to enhance data strategy.

Design, implement, and optimize data quality management solutions and governance workflows. Collaborate with data product managers, business SMEs, and engineering to improve data quality, discoverability, lineage, and compliance. Support tool implementation (Anomalo, metadata tools), run data profiling/cleansing, document standards, enable users through training, and participate in Agile delivery and backlog prioritization.

Design, configure, and operate data governance tooling for unstructured and structured data. Implement metadata cataloging, lineage harvesting, automated data quality checks, and governance workflows. Build prototypes, dashboards, and connectors using Python, SQL, Databricks, and Streamlit. Collaborate with stakeholders to define critical data elements, prioritize remediation, produce documentation, and drive tool adoption via trainings and enablement.