Top Hybrid Data & Analytics Jobs

Lead the architecture and implementation of scalable GCP and Databricks data lakehouse platforms. Design batch and real-time pipelines, data models, governance, cataloging, security, and performance strategies. Act as a technical lead and trusted client advisor while mentoring engineers, guiding architecture decisions, conducting proofs of concept, and supporting hands-on troubleshooting and delivery.

Collects, cleans, validates, and analyzes data from multiple sources. Develops dashboards, reports, and visualizations using SQL, Excel, Power BI, or Tableau. Identifies trends, monitors data quality, supports KPI tracking, and delivers actionable insights for business decisions. Collaborates with stakeholders, documents analytical processes, prepares regular and ad hoc reports, and recommends process improvements based on data.

Leads the technical strategy, architecture, engineering, and delivery of industrial data solutions. Oversees data engineering teams, current warehouse reliability, Databricks lakehouse migration, ERP data migration from SAP ECC and legacy platforms to SAP S/4HANA, and data governance standards. Develops multi-year roadmaps, establishes engineering practices, manages contractors and vendors, and partners with business, finance, SAP, and technology leaders to deliver scalable, reliable data products.

Lead and grow Stash’s Data Engineering team while owning the AWS data platform roadmap. Improve reliability, observability, incident response, automation, CI/CD, infrastructure as code, data quality, security, and cost management. Guide ingestion, distributed processing, storage, warehouse delivery, and real-time pipelines. Partner with engineering, SRE, analytics, data science, and business stakeholders to establish ownership, reliable data contracts, and maintainable architecture.

Build and maintain reporting suites, dashboards, analytical models, and quantitative analyses that support business decisions. Partner with leaders across Operations, Risk, Servicing, Finance, Product, and Sales to investigate complex questions, generate actionable insights, and identify growth opportunities. Collaborate with data engineers to ensure accurate data delivery while managing multiple cross-functional projects and communicating findings through clear, persuasive narratives.

Advance enterprise data governance by analyzing and improving business and data-management processes, facilitating cross-functional stakeholder sessions, translating policies into workflows and controls, and supporting data quality, access governance, data sharing, lineage, cataloging, and data product initiatives. The role requires extensive requirements elicitation, process documentation, stakeholder facilitation, SQL, database, and data warehouse experience.

Leads enterprise data architecture strategy, roadmap, and implementation across data models, pipelines, lakes, warehouses, and business intelligence. Establishes governance, quality, security, and compliance standards; evaluates emerging technologies; collaborates with business and IT stakeholders; mentors data professionals; resolves complex data challenges; and maintains architecture documentation.

Provides business analysis across institutional or enterprise initiatives by gathering requirements, analyzing costs, benefits, and risks, documenting objectives, supporting functional specifications, validating solutions, and coordinating project deliverables. Collaborates with stakeholders, applies business analysis and systems engineering methodologies, performs data analysis, and may manage limited-complexity projects. The role requires a bachelor’s degree with four years of experience or a master’s degree with two years of experience.

Coordinates and manages survey research projects, including questionnaires, methodologies, timelines, budgets, and project documentation. Develops client and industry knowledge, analyzes and interprets research results, and contributes to reports, presentations, and data visualizations. Collaborates across departments and supports clients in the public sector and health industries. Requires research experience, quantitative analysis skills, strong communication, attention to detail, teamwork, and proficiency with Microsoft Office.

Build and evolve scalable AWS data platforms, enterprise data warehouses, pipelines, schemas, and data models. Maintain Redshift and related technologies, monitor and optimize data jobs, implement data quality and alerting, and improve lineage and documentation. Partner with analytics, data science, and business teams to deliver reliable datasets. Participate in Agile development, code reviews, mentoring, automation, and continuous improvement.