Top Data Management Jobs in NYC, NY

Own customer analytics and data infrastructure across Shopify, CDP, CRM, and cloud data warehouse systems. Build segmentation, dashboards, retention and lifetime-value analyses, and predictive models using SQL and Python. Maintain data quality, identity resolution, governance, and audience activation while partnering with marketing, ecommerce, merchandising, and CRM teams. Present actionable customer insights and recommendations to technical and executive stakeholders.

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.

Leads a team of 5–8 data engineers and analysts while remaining hands-on with Databricks and Azure data platforms. Owns scalable pipelines, Lakehouse architecture, data products, quality, governance, reliability, security, and cost management. Oversees hiring, coaching, performance, delivery prioritization, agile execution, production health, incident response, stakeholder communication, and cross-team collaboration. Helps shape global data engineering strategy, standards, technology adoption, and platform evolution.

Leads Fetch’s centralized Operations Analytics team, establishing standards, operating models, KPI definitions, dashboards, and reporting practices. Manages and develops Operations Data Analysts, partners with senior operational leaders, and delivers insights supporting strategy, staffing, process improvement, and decision-making. Oversees reporting in Hex, Tableau, and Grafana; improves data quality and automation with engineering; and translates ambiguous operational data into measurable recommendations and business outcomes.

Leads data analysis strategy for an analysis platform product, including data mining, modeling, testing, reporting, process improvement, and product analytics. Manages junior analysts, mentors team members, collaborates across business units, and supports large-scale databases and data storage systems. The role includes business intelligence, strategic experimentation, operational efficiency improvements, and consulting on production and data system design.

Owns and maintains organizing data systems, voter-contact tools, and organizational databases. Ensures data integrity through quality assurance, audits, standardized processes, documentation, and permission management. Supports organizers by troubleshooting tools, managing data requests, providing training, and improving workflows. Writes SQL queries in BigQuery, develops reports and visualizations, supports integrations, and collaborates with engineering and analytics teams on data models and priorities.

Manages client, compliance, and performance reporting across healthcare programs using eligibility and claims data. Leads reporting analysts while remaining hands-on with advanced SQL, dashboards, data crosswalks, validation, reconciliation, root-cause analysis, and data-quality monitoring. Partners with data engineering and clients to resolve upstream issues, establish reporting standards, and guide the analytics roadmap.

Leads enterprise ontology and data-modeling strategy, governance, integration, standardization, and roadmap development. Manages teams creating semantic models, taxonomies, linked data, and reusable capabilities while partnering with technology, machine learning, and business stakeholders. Advocates W3C standards, supports knowledge organization workshops, establishes modeling guidelines, monitors industry trends, and mentors team members. Requires expertise in metadata, ontologies, linked data tools, graph technologies, SQL or SPARQL, and semantic standards.

Leads the architecture and implementation of Nokia’s scalable data platforms for photonic integrated circuit operations. Responsibilities include developing lakehouse and warehouse solutions, data models, batch and streaming pipelines, data quality and observability frameworks, CI/CD and DataOps practices, governance, security, and AI-ready data foundations. The role also leads and mentors product engineering teams, enables secure self-service analytics, and drives enterprise data excellence and innovation.

Build and lead Inovalon’s third-party data governance program, including data asset inventory, licensing controls, contractual rights management, data intake and release governance, audit readiness, compliance monitoring, and KPI reporting. Partner with Legal, Privacy, Procurement, and business leaders to manage data usage, renewals, access revocation, disposition, and downstream obligations. Develop a governance team while applying expertise in healthcare data, HIPAA, de-identification, and data licensing.

Leads marketing data analysis, audience segmentation, campaign targeting, and performance insights using SAS, SQL, Python, Databricks, and Salesforce Data Cloud. Translates marketing strategies into campaign specifications, develops and activates customer audiences, validates targeting logic, and communicates recommendations to marketing, business, compliance, and technology stakeholders. The role improves targeting methodologies, supports campaign execution, identifies growth opportunities, and provides specialized business insights while ensuring governance and regulatory alignment.

Owns data integrity, quality assurance, remediation, standards, and governance for Development data. Leads audits, maintains data definitions and business rules, assigns corrective actions, facilitates governance decisions, and partners with analytics, CRM, fundraising, finance, IT, compliance, and legal teams. Develops training, monitors stewardship accountability, resolves data-quality issues, and ensures reliable reporting and downstream business processes.

Leads the Health Fund’s Data Engineering Team and oversees enterprise data warehouses, pipelines, integrations, governance, testing, and data quality initiatives. Provides technical leadership, manages staff, translates business requirements into scalable solutions, and partners with business, technology, QA, infrastructure, and external vendors. Ensures data platforms meet performance, reliability, privacy, security, regulatory, and operational requirements while developing data strategy, architecture, documentation, standards, and best practices.

Leads a team of data analysts supporting Marketing, Digital, Customer, and DEI functions. Oversees dashboards, reporting, advanced analytics integration, data requirements, quality assessment, visualization, and business insights. Partners with Data Science, Data Engineering, Technology, business units, and vendors to translate requirements into actionable solutions and drive analytics adoption. Coaches analysts, manages priorities, and supports strategic use cases using SQL, Python, cloud data platforms, experimentation, and business intelligence tools.

Leads data analytics and business intelligence strategy, mining large datasets, building and validating models, improving processes and reporting, evaluating products and initiatives, and consulting on data systems. Manages and mentors junior analysts, collaborates across business units, and oversees projects from inception through completion. The role requires advanced analytical, programming, communication, leadership, and problem-solving skills.

Own Pursuit’s data infrastructure, semantic layer, data dictionary, reporting, dashboards, and AI-enabled capabilities. Improve data quality and self-service access while designing structures with cross-functional teams. Establish data governance for reliable human and AI-agent use, evaluate AI workflows, integrate SaaS systems, and administer permissions and workflows. The role requires hands-on technical work, cross-functional project management, stakeholder communication, and high ownership of scalable data systems.

Leads and scales Anthropic’s Data Warehouse and Streaming Infrastructure team. Responsibilities include managing and mentoring engineers, owning batch and streaming data platforms, setting technical strategy, improving reliability, security, governance, cost, and data quality, establishing SLAs, partnering across business functions, making infrastructure decisions, and hiring senior data infrastructure engineers. The role requires deep expertise in warehousing, pipelines, orchestration, event streaming, change data capture, distributed systems, and multi-cloud platforms.

Own the company-wide BI strategy, infrastructure, governance, dashboards, LookML models, forecasting, and analytics request process. Partner with executives, business owners, Data Engineering, Product, and Engineering to improve data reliability, translate business questions into recommendations, and surface trends and opportunities. The role requires SQL, BI tooling, and data warehouse expertise, with Python, predictive modeling, and statistical analysis preferred.

Designs, builds, tests, and supports enterprise data pipelines and Snowflake archival solutions for acquisitions, integrations, reporting, compliance, and analytics. Translates business and technical requirements into mappings, transformations, quality rules, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams. Oversees validation, monitoring, documentation, cutover, go-live readiness, hypercare, and operational handoff while improving reusable, secure, cost-efficient data engineering practices.

Leads data governance for acquired-company integrations, embedding ownership, stewardship, quality, metadata, lineage, retention, privacy, legal holds, and compliant data use across structured and unstructured content. Establishes data inventories, quality rules, retention and disposal processes, governance controls, and readiness metrics. Partners with business, technology, legal, privacy, risk, security, and implementation teams, while producing executive reporting and supporting governance technology adoption.

Lead development and delivery of analytical datasets and AI-enabled analytics for global real estate. Partner with stakeholders to translate business needs, design data solutions, enforce governance and quality, scale AI use cases, and deliver executive-level reporting and project management.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Lead data strategy, architecture, and modeling for high-volume transactional network platforms. Build monitoring and anomaly-detection frameworks, optimize operational data schemas, align local assets with enterprise data strategy, communicate findings to stakeholders, and mentor technical staff.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.