Top Senior Data Management Jobs in Boston, MA

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 Motorsports Data Infrastructure and Data Science teams while owning the strategy, architecture, and delivery of data platforms supporting telemetry, simulation, trackside, analytics, and AI/ML use cases. Responsibilities include managing managers, designing streaming and batch pipelines, productionizing ML models, setting engineering standards, managing Azure and Databricks capacity, protecting sensitive data, and partnering with racing and executive stakeholders. The role remains hands-on in architecture, coding, code review, incident support, and technical problem-solving.

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.

Leads enterprise data management, governance, quality, lifecycle, metadata, stewardship, database, and repository activities. Develops data policies and standards, resolves complex data issues, oversees migration and integration efforts, ensures compliance and access controls, and improves data reliability across systems. Partners with executives, technical teams, analysts, cybersecurity, and compliance stakeholders while providing leadership to staff and preparing senior-management briefings. Requires expertise in SAS, SQL, AWS, and data-intensive domains, with medical or Military Health System data experience preferred.

Leads enterprise data management, governance, quality, lifecycle, metadata, stewardship, database, and repository activities. Develops policies and standards, oversees data integrity and access, resolves complex data issues, supports migrations and integrations, and ensures compliance with security and contractual requirements. Partners with executives, technical teams, analysts, and stakeholders while providing leadership to data staff. Uses SAS, SQL, and AWS to manage and optimize large-scale data, preferably including Military Health System records.

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.

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 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 and operate Toast’s enterprise data governance program, including data domain ownership, governance council coordination, policy compliance, business glossary management, metadata standards, catalog adoption, maturity assessments, and data literacy training. The role partners with business stakeholders, data stewards, catalog teams, and leadership to improve data trust, compliance, discoverability, and quality. It requires governance, metadata, SQL, data catalog, program management, and workshop facilitation experience.

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 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.

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.

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.

Manages the enterprise ETL practice and data integration architecture. Designs and supports Informatica integrations, data synchronizations, APIs, Oracle SQL procedures, Salesforce workflows, Marketing Cloud data extensions, and Data Cloud components. Collaborates with technical teams and business partners, monitors and optimizes integration operations, troubleshoots issues, improves quality assurance, provides technical guidance and staff training, and contributes to integration policies and plans.

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 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.

Manages research data acquisition, licensing, vendor relationships, contracts, data use agreements, governance, and compliance. Leads data safety reviewers, assesses privacy and contractual risks, develops SOPs and access workflows, trains researchers, and coordinates with faculty, vendors, legal counsel, procurement, compliance offices, and university stakeholders.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Leads regional data analytics delivery for Global Business Services, including advanced analysis, reporting, dashboards, KPI frameworks, data governance, and executive decision support. Provides indirect leadership to analysts, establishes analytical standards, supports procurement and sourcing initiatives, evaluates supplier proposals, drives automation and continuous improvement, manages third-party analytics platforms, and develops training to improve adoption and analytics maturity.

Designs, builds, tests, and supports enterprise data pipelines for acquired-company system integration and Snowflake archival. Translates business and technical requirements into mappings, transformations, quality controls, monitoring, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams to deliver governed, reusable data solutions. Supports migration, cutover, validation, documentation, hypercare, and operational handoff while improving automation, performance, cost efficiency, and data observability.