Top Hybrid Data & Analytics Jobs

Design and operate scalable data pipelines, transformation workflows, layered data models, and production data infrastructure supporting analytics, experimentation, and AI/ML. Implement monitoring, data quality, observability, and incident response processes; modernize legacy systems; collaborate with product, analytics, and engineering teams; and mentor engineers through reviews and architectural discussions.

Design, build, and optimize internal data platforms, automated pipelines, semantic layers, and scalable data models. Develop production-grade Python and SQL code, ensure CI/CD and uptime, perform code reviews and debugging, partner with stakeholders to translate requirements, and own the end-to-end technical product lifecycle for analytics and BI tools.

Supports commercial market intelligence through market, customer, competitor, and industry research. Analyzes qualitative and quantitative data, creates dashboards and presentations, identifies growth opportunities, and develops actionable insights for commercial decision-making. The intern also explores artificial intelligence, generative AI, and automation to improve research and reporting workflows, while completing a manager-assigned project and presenting recommendations to stakeholders.

Leads the GIS data management function, supervising analysts, technicians, and contractors responsible for mapping, data maintenance, and QA/QC. Establishes geospatial data quality metrics, dashboards, SLAs, and corrective actions; manages workflows, process improvements, vendors, budgets, staffing, and professional development. Collaborates with cross-functional stakeholders to maintain enterprise GIS data integrity and support utility operations.

Develop quantitative market insights through market sizing, forecasting, competitive intelligence, segmentation, and trend analysis. Build analytical models using internal and external data, manage market research engagements, and translate findings into strategic recommendations. Partner with Marketing, Finance, Strategy, and other stakeholders while creating executive-ready presentations and scalable market insights processes.

Aggregates enterprise data, builds advanced financial models, and delivers analytics, dashboards, reports, and executive insights supporting growth initiatives. Develops conversational and workflow agents using Claude, Microsoft Copilot Studio, Snowflake, and Salesforce; automates reporting and data distribution; and partners with stakeholders to define requirements. The role leads analytical projects from ideation through executive presentation and supports forecasting, advisor economics, growth ROI, and operational efficiency initiatives.

Leads market sizing, forecasting, competitive intelligence, segmentation, and quantitative analysis for Stryker Medical. Develops market models, evaluates trends and opportunities, conducts primary and secondary research, manages external research vendors, and translates complex data into executive-ready insights. Partners with Marketing, Finance, Strategy, Business Development, and other stakeholders to support strategic planning, portfolio decisions, and growth initiatives while establishing scalable market-insights processes and tools.

Leads enterprise Data and AI platform governance, operations, adoption, optimization, security, and compliance. Manages analytics strategy and team performance while overseeing data pipelines, predictive models, analytical databases, and workflows. Partners with technical and business stakeholders to translate needs into solutions, improve platform value, establish standards, and support responsible innovation. Responsibilities include recruiting, coaching, mentoring, cost optimization, vendor management, and communicating complex technical findings to diverse audiences.

Leads enterprise data architecture strategy, standards, governance, and technical direction while managing data architecture professionals. Oversees data models, databases, integration platforms, cloud data environments, security, privacy, lineage, metadata, and data quality. Guides scalable, AI-ready platforms supporting reporting, analytics, machine learning, Power BI, and Microsoft Copilot. Partners with business, technology, cybersecurity, and data governance stakeholders while balancing strategic architecture with operational delivery.

Leads Healogics’ data engineering team and enterprise data platform strategy. Owns SQL Server warehouse reliability, ETL, OLAP, SSRS, data architecture, modeling, governance, security, and production support while directing migration to Databricks. Translates business needs into scalable data solutions, establishes engineering standards, manages vendors and implementation partners, and partners with executives, analytics, application, cybersecurity, and infrastructure teams.