Top Data & Analytics Jobs in NYC, NY

Build and architect scalable cloud data platforms, pipelines, and applications using Python, Spark, SQL, Databricks, Snowflake, and relational or NoSQL databases. Design secure, resilient, and reusable data engineering solutions; support distributed and streaming workloads; enforce engineering standards; collaborate with product, software, analytics, and data science teams; communicate technical concepts; and mentor other engineers.

Build and architect scalable cloud data solutions, pipelines, platforms, and data products. Lead large-scale data initiatives, make architecture and platform decisions, ensure performance and operational efficiency, and apply modern technologies such as Python, Spark, Databricks, and Snowflake. Collaborate with Agile teams, product managers, software engineers, analysts, and data scientists while mentoring engineers and communicating technical concepts to stakeholders.

Lead product analytics for Enterprise Data products, validating analytical tools, assessing methodology risks, researching emerging practices, and translating complex data into actionable insights. Manage validation projects, communicate findings through reports and presentations, and coach junior staff. The role requires advanced data analysis, statistical or econometric modeling, predictive analytics, large-dataset analysis, data governance, and people leadership.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Collaborate with Agile teams, product managers, engineers, analysts, and data scientists while applying Python, Spark, SQL, Databricks, Snowflake, relational and NoSQL databases. Establish reusable engineering patterns, data security controls, and resilient architectures. Mentor data professionals, communicate technical concepts to stakeholders, and deliver user-centric data solutions with minimal supervision.

Leads product analytics for Retail Bank growth, using SQL, Python, R, experimentation, causal inference, statistical modeling, segmentation, and data storytelling. Partners with Product, Engineering, Finance, and Research to shape roadmaps, prioritize opportunities, establish KPI standards, and influence investment and product decisions.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Build and operate scalable cloud data platforms, pipelines, and applications using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Design data models, enforce engineering patterns and security standards, support distributed and streaming workloads, and deliver resilient solutions. Collaborate with product managers, software engineers, analysts, and data scientists while mentoring teammates and communicating technical concepts to stakeholders.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Collaborate with data scientists, analysts, engineers, and product managers while applying distributed computing, lakehouse architecture, data modeling, security, and observability practices. Develop resilient relational and NoSQL data solutions, mentor team members, enforce engineering standards, and communicate technical outcomes to stakeholders. The role requires independent delivery of cloud-first data products supporting large-scale financial experiences.

Own analytics engineering and the data transformation layer by designing data models, warehouses, cubes, semantic layers, and governance frameworks. Improve data quality, observability, metadata, self-service analytics, dashboards, and reporting platforms. Analyze large datasets, optimize queries, conduct testing and code reviews, support modernization initiatives, and collaborate across teams to deliver trusted metrics and insights.

Analyze commercial banking challenges and opportunities, develop strategic recommendations, model lending and pricing strategies, assess credit risk and portfolio performance, support new product launches, and collaborate with IT, Sales, Operations, and Finance to improve profitability and growth.