Top Data & Analytics Jobs

Leads Vitana’s data and technology strategy by building centralized data architecture, warehouses, pipelines, integrations, reporting, and governance. Serves as the technical leader across IT infrastructure, vendors, security, compliance, and technology implementations. Partners with executives and practice leaders to translate business needs into scalable solutions, improve data quality, support practice integrations, and connect technology investments to operational and financial outcomes.

Own and evolve WorkOS’s internal data platform, including ingestion, orchestration, Snowflake, dbt models, data governance, reverse ETL, semantic views, and AI-enabled data workflows. Ensure pipeline reliability, freshness, security, and scalability while partnering with Product, Finance, RevOps, GTM, Engineering, and Security. Build monitoring, runbooks, CI/CD gates, access controls, masking policies, and infrastructure automation across AWS and Kubernetes.

Two-year early-career rotational program with three cross-functional assignments focused on data engineering and analytics. Participants create analytical reports, work with machine learning and artificial intelligence, lead intensive business projects, and develop technical, interpersonal, and leadership skills. The program provides exposure to the full data lifecycle, business strategy, and continuous improvement, with potential placement into a post-program role.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

Supports Massachusetts DPH enterprise data modernization by gathering and documenting business, process, workflow, and data requirements. Serves as liaison between public health programs and technical teams, supports data onboarding to the Enterprise Data Platform, facilitates stakeholder workshops, defines requirements for dashboards and data products, validates solutions, and develops business analysis standards and documentation.

Leads the design, development, governance, and optimization of enterprise BI solutions using Power BI, DAX, data modeling, and automation. Builds scalable datasets, dataflows, and semantic models; improves performance; manages deployments, security, and documentation; partners with stakeholders and data engineers; and mentors analytics developers.

Manages multiple quantitative market research projects from inception through delivery. Responsibilities include questionnaire development, fieldwork management, data processing and multivariate analysis oversight, data synthesis, report creation, quality-checking toplines and reports, and mentoring Junior Project Directors. The role translates research findings into actionable business insights for clients and operates fully remotely within Eastern Time Zone business hours.

The posting provides application instructions for an Enterprise Applications, Data and Analytics Manager role but does not describe specific responsibilities, qualifications, technologies, compensation, travel, or clearance requirements.

Design and develop scalable backend services, APIs, data ingestion solutions, ETL workflows, and data pipelines. Perform data modeling, mapping, and large-scale file manipulation while optimizing systems for speed and scalability. Collaborate in an Agile environment, apply LLMs to enrich data, and work with distributed systems, NoSQL databases, cloud platforms, and AI tooling. An active TS/SCI clearance with full-scope polygraph is required.

Support database health, performance, availability, maintenance, troubleshooting, access management, documentation, SQL optimization, automation, migrations, replication, and disaster recovery testing. Collaborate with engineers and analysts while learning database performance tuning and operational best practices.