Top Senior Data Management Jobs in Boston, MA

Leads client-facing data validation and risk workstreams, developing reliable data pipelines, integrations, transformations, and validation controls. Manages project plans, budgets, timelines, deliverables, and team performance while analyzing data structures and system interactions to identify risks. Coaches team members, collaborates with stakeholders, improves database and query performance, promotes automation and AI-enabled tools, and ensures technical standards, documentation, and independence requirements are maintained.

Leads Customer Success analytics strategy, executive business reviews, customer experience and voice-of-customer insights, enablement impact measurement, and data foundation development. Manages two analysts, partners with data engineering and data science, applies statistical and experimental methods, analyzes structured and unstructured customer data, and uses AI tooling to improve self-service and recurring analytics. Translates ambiguous business questions into actionable recommendations for senior leaders.

Leads end-to-end business intelligence and advanced analytics solutions, translating business questions into trusted datasets, dashboards, semantic models, and actionable insights. Partners with stakeholders to establish measurable outcomes and a single source of truth. Performs data discovery, SQL optimization, statistical analysis, data modeling, ETL, and data quality controls while delivering scalable Power BI and Tableau products.

Manages government program data, CDRL deliverables, records, document control, file plans, databases, and SharePoint environments. Responsibilities include developing data standards, maintaining repositories, administering database systems, supporting data warehousing and mining, monitoring data capacity and performance, and ensuring compliance with information security policies. The role supports multiple defense acquisition and sustainment programs, coordinates with government and contractor stakeholders, and requires onsite work at Hanscom Air Force Base.

Leads CHA’s organization-wide data strategy, warehouse development, reporting, and dashboarding initiatives. The role designs data models and pipelines, integrates information from multiple systems, develops Power BI dashboards, establishes documentation standards, manages vendors, and guides departmental data roadmaps. It also partners with senior leaders to gather requirements, drive adoption, improve data quality, and build a reliable, data-informed organization.

Lead dataset onboarding for Fidelity’s Quantitative Research Platform. Integrate and curate financial and alternative datasets, establish data quality and governance standards, and design consumption patterns with researchers and technology partners. Lead and coach engineering teams, improve documentation and onboarding processes, and deliver scalable data solutions for quantitative investment research. The role requires SQL, Python, financial data expertise, vendor data experience, point-in-time modeling, historical reconciliation, and strong cross-functional collaboration.

Leads data engineering architecture and modeling initiatives, designing scalable pipelines, cloud data platforms, and reusable data solutions. Collaborates with engineering, product, analytics, and data science teams while mentoring developers and establishing common design patterns. Responsibilities include distributed data processing, relational and NoSQL systems, data security, observability, streaming pipelines, and operational excellence across platforms such as Databricks and Snowflake.

Lead and mentor a product analytics team that diagnoses product performance, evaluates launches, defines trusted KPIs, and drives strategic decisions. Oversee rigorous experimentation, causal inference, cohort analysis, metric governance, and telemetry standards. Partner with Product, Engineering, Marketing, Growth, Design, and Finance leaders to translate analysis into recommendations. Promote AI-native workflows using tools such as Claude Code while ensuring analytical quality, code validation, and clear executive communication.

Manages research data acquisition, licensing, contracts, vendor relationships, governance, and compliance at Harvard Kennedy School. Leads data safety staff, evaluates contractual and privacy risks, develops data management plans and SOPs, oversees access and disposition workflows, and advises researchers and institutional stakeholders on data-use obligations, regulatory requirements, and risk mitigation.

Manages program data, CDRL deliverables, records, document control, file plans, databases, data standards, and SharePoint environments for Air Force acquisition programs. Responsibilities include database design and administration, data repositories, records management, reporting, cybersecurity compliance, SharePoint configuration, site administration, usage monitoring, and end-user support. The role coordinates with government and contractor stakeholders across multiple DoD programs and requires onsite work at Hanscom Air Force Base.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Leads the design, delivery, and optimization of data architecture, pipelines, semantic layers, data quality frameworks, and Tableau BI platforms. Partners with stakeholders to manage requirements, project plans, sprint execution, monitoring, governance, and release delivery. Guides data engineers, manages team members, and supports AI-enabled analytics capabilities. Requires strong SQL, Spark, PySpark, SSIS, cloud data platform, CI/CD, Tableau infrastructure, and data engineering expertise.

Leads and grows the data engineering team while owning enterprise data architecture, ingestion, modeling, semantic layers, governance, secure APIs, and reliable platform outcomes. Partners with finance, operations, sales, marketing, and product to deliver governed, traceable data for products and AI agents. Sets the roadmap, manages vendors and costs, reviews architecture, contributes code, and delivers cross-functional data platform projects.

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.

Owns the Source-to-Pay data and analytics foundation, including master data, taxonomy, governance, quality, analytics products, automation, and AI readiness. Leads business requirements, operating models, executive dashboards, KPI frameworks, decision-support insights, and cross-functional platform enablement. Partners with Procurement, Finance, Legal, Risk, IT, and enterprise data teams to improve data reliability, controls, reporting, self-service analytics, and scalable automation.

Generate actionable customer and product insights by synthesizing large, complex datasets, developing hypotheses, conducting experimentation and analysis, and translating findings into strategic business decisions. Collaborate cross-functionally with analytics, engineering, data science, marketing, and product teams. Build dashboards and reports, identify trends and growth opportunities, communicate customer experience insights, and strengthen analytics capabilities across the organization.

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.

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.

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.

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.

Leads the development and operationalization of governed clinical and multi-omics data products for neuroscience research. Designs scalable data models, optimizes Nextflow pipelines across AWS S3, Snowflake, and TileDB, standardizes assay outputs, embeds FAIR principles and compliance, and delivers AI-ready datasets. Partners with architects, governance teams, AI/ML specialists, and data scientists while mentoring engineers and driving workflow standardization, quality, reproducibility, and pipeline optimization.

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.