Top Senior Data Management Jobs in Boston, MA

Leads applied AI and health data architecture initiatives for payer clients. Designs cloud-native platforms, pipelines, data models, integrations, and modernization roadmaps across AWS, Azure, Databricks, and Snowflake. Oversees data quality, governance, anonymization, performance optimization, and legacy migrations while advising stakeholders on AI-ready architectures. Manages multi-team delivery, resolves technical issues, presents solution tradeoffs, and coaches practitioners.

Leads and manages a business analyst team supporting a data platform. Partners with clients, product managers, engineers, and stakeholders to gather requirements, write user stories, perform data gap analyses and source-to-target mapping, validate data using SQL, and support data quality, lineage, QA, Agile delivery, change management, and documentation. Requires healthcare data expertise, people leadership, strong communication, and experience translating technical information for varied audiences.

Lead large-scale data engineering initiatives, designing scalable cloud data platforms, pipelines, and architectures. Use Python, Spark, SQL, Databricks, Snowflake, AWS, relational and NoSQL databases to deliver resilient data solutions. Mentor engineers, analysts, and data scientists; establish engineering standards; evaluate platform choices; and collaborate with product and software teams to support enterprise data transformation and AI capabilities.

Leads end-to-end business intelligence and analytics solutions, translating complex business questions into trusted datasets, dashboards, semantic models, and actionable insights. Partners with senior stakeholders, performs advanced SQL and statistical analysis, establishes data quality controls, and guides BI product delivery using Power BI, Tableau, Python, and cloud data platforms. The role requires financial services experience, strong data storytelling, analytics engineering, data modeling, and consultative communication skills.

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.

The Manager, R&D Data Modeler designs and governs conceptual, logical, and physical data models for R&D analytics and digital initiatives. Responsibilities include source-to-target mapping, schema optimization, data integration, metadata and naming standards, FAIR and GxP governance, model versioning, architecture workshops, platform implementation consulting, and mentoring junior modelers. The role supports scalable, interoperable data ecosystems for analytics and AI workloads across data warehouses and cloud data lakes.

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.

Owns go-to-market data governance, quality, enrichment, and automation across Salesforce and connected systems. Designs standards, controls, source-of-truth models, AI and LLM-powered workflows, monitoring, and remediation processes. Partners with Business Operations, Marketing Operations, Customer Success, Finance, IT, and security to improve data accuracy, compliance, reporting, and operational efficiency. Leads data management and automation projects from planning through measurable outcomes.

Coordinates Oracle EPM Cloud data governance, metadata management, integrity reviews, reconciliations, restatements, reporting controls, audit support, and system enhancements. Partners with Finance, Accounting, IT, and business stakeholders to resolve data variances, document requirements, support SOX compliance, maintain reporting outputs, and improve enterprise financial reporting processes.

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 end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages sprint planning, releases, DevOps metrics, project delivery, and stakeholder communication. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, and ensures reliable, well-documented data solutions that support organizational reporting and analytics needs.

Leads the enterprise business intelligence and analytics strategy, manages BI and data analysts, and oversees analytics roadmaps, projects, platforms, dashboards, and vendor relationships. Translates complex data into actionable financial and business insights, supports SAP and Power BI platform upgrades, manages delivery timelines and resources, and coaches team members. The role also drives stakeholder engagement, continuous improvement, talent development, and data-driven decision-making across the organization.

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.

Owns Kestra’s enterprise data platform, Microsoft Fabric transition, data architecture, governance standards, and Master Data Management program. Leads platform reliability, semantic models, self-service BI enablement, data protection, compliance, vendor resources, and technical teams. Advises executives and functional data owners while preparing governed data assets for AI, automation, and enterprise reporting.

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.