Top Senior Data Management Jobs in NYC, NY

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Manage and grow Ashby’s data analytics team while remaining hands-on with analytical work. The role includes hiring and coaching analysts, improving data practices, prioritizing requests, developing specialization, maintaining analytical quality, and guiding responsible AI adoption. The manager will work across raw and modeled data, dbt models, metric definitions, dashboards, and internal data products, partnering closely with business teams in a remote, high-growth B2B SaaS environment.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Build and support production-grade Microsoft Fabric data products and pipelines across ingestion, transformation, lakehouse, warehouse, and curated layers. Implement reliable, restartable, and observable data solutions using medallion architecture, automated testing, governance, lineage, monitoring, CI/CD, and DataOps practices. Collaborate with architects, analytics, governance, application, and partner teams while documenting mappings, runbooks, controls, and operational procedures.

Leads analytics initiatives, data modeling, executive dashboard development, KPI reporting, forecasting, predictive modeling, experimentation, and AI-assisted analytics. Partners with Marketing, Content, Product, Engineering, and leadership to translate complex data into strategic recommendations. Owns Sigma reporting, data definitions, downstream dbt models, and data quality efforts while mentoring junior analysts.

Lead design and implementation of data infrastructure, pipelines, and warehouses using Azure Data Factory, Databricks, and Snowflake. Manage data modeling, quality, security, and analytics frameworks. Lead client accounts, mentor teams, and drive innovation to deliver data-driven business insights.

Lead and coach teams to design, code, test, and deliver software solutions driving digital transformation for tax clients. Translate requirements into technical specs, perform code reviews, troubleshoot complex issues, maintain client relationships, and promote innovation and systems thinking to validate outcomes and improve products.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Leads client-focused data analytics initiatives within PwC’s Risk & Regulatory practice. Develops business intelligence, visualization, and advanced analytics solutions using Python, Oracle Business Intelligence, QlikView, and Spotfire. Builds stakeholder relationships, validates outcomes, drives process improvement, and applies systems thinking to solve complex business challenges. Oversees scalable deployments and coaches teams through ambiguous situations while delivering strategic insights and improved client performance.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Leads data analytics projects that generate insights for strategic decision-making. Develops visualization solutions with Power BI and Tableau, builds data pipelines, applies statistical modeling and predictive analytics, and manages data integrity and security. Collaborates with clients on tailored data solutions while coaching analytical teams, managing accounts, overseeing project success, and identifying business opportunities.

Own the go-to-market master data management roadmap and governance model for accounts, contacts, and organizational hierarchies. Define golden record, matching, merging, survivorship, data quality, stewardship, and SLA standards across Salesforce, billing, finance, marketing, product, support, and warehouse systems. Partner with engineering, systems, finance, legal, and security teams to implement integrations, privacy controls, data products, and remediation programs. Report data health, risks, and business impact to leadership.

Manage and develop a team of 4–6 analysts delivering customer reporting and analytics. Lead complex analyses, establish standards for rigor and reproducibility, oversee project delivery, present findings to stakeholders, and partner with Product and Engineering on measurement products and AI-enabled analytics tools. The role requires deep advertising measurement expertise, client-facing communication, dashboard development, and hands-on proficiency in SQL, Python, Excel, statistical methods, and analytics platforms.

Leads Garner’s Data Platform Engineering team, overseeing scalable healthcare data infrastructure, pipelines, abstractions, and distributed processing systems. Provides hands-on architectural guidance, establishes engineering standards, translates business requirements into technical roadmaps, and promotes AI-native development practices. The role includes hiring, mentoring, stakeholder management, design reviews, root cause analysis, and operational excellence while supporting rapid enterprise data growth.

Lead the Underwriting Data Analyst team supporting pharmaceutical underwriting, pricing, sales, and client retention. Manage analysts, oversee data collection and quality, develop SQL, Python, and R infrastructure, create analyses and reporting, support pricing models, review analytical outputs, and coordinate cross-functional initiatives. Train team members, manage work queues, document processes, and provide subject-matter expertise on underwriting data and systems.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, and segmentation. Partners with Marketing and Finance to establish performance goals and translate complex data into actionable recommendations. Automates reporting using analytics platforms, marketing automation tools, experimentation methods, and AI-enabled workflows while identifying opportunities to grow and retain high-value consumers.

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 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.

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.

Lead and implement hands-on data governance across the Data Platform: build and operate the enterprise catalog, automate lineage, embed data quality checks, configure Snowflake governance, manage access workflows and event contract governance, create governance metrics and dashboards, define standards and operating model, enable domain teams, and hire and lead a small governance function.

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.

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.