Top Data & Analytics Jobs

The Data Engineer will build and maintain scalable data pipelines, improve ETL processes, collaborate with AI/ML teams, and contribute to engineering culture.

Lead analytics and BI for Digital Product Operations: define product and adoption metrics, build dashboards, ensure data governance and quality, measure ProdOps effectiveness, coach PM/POs, diagnose adoption gaps, and drive interventions that improve product planning and delivery.

The Data Engineer at Anteriad will design, build, and optimize data pipelines, manage data integration processes, support analytics efforts, and collaborate with stakeholders to deliver scalable data solutions.

Manage a team responsible for data ingestion, extraction, mapping, enrichment, QA/QC, and automation. Build and maintain Alteryx/Power Automate/Python workflows, manage APIs and feeds, track KPIs/SLAs, recruit and cross-train staff, and drive process improvements across public, private, and operational asset classes while partnering with cross-functional teams.

Lead and grow a data engineering team; define architecture and standards for ETL/ELT pipelines; hands-on design, code review, and development; ensure production reliability, monitoring, and incident response; partner with product and engineering on data roadmap.

Lead analytics for the 340B Prime Vendor Program: analyze purchasing and contract data, build dashboards and KPIs, perform quantitative and financial analyses, query databases, and translate insights for stakeholders to optimize contracts and sourcing strategies.

Lead data operations reporting and deep-dive analysis to improve data quality, customer experience, and operational health. Aggregate data from multiple sources, present actionable recommendations to leadership, partner with stakeholders on solutions and enterprise initiatives, and mentor junior team members.

Extract, transform, and report EHR data by writing complex SQL queries, building reusable reports and dashboards (Excel, Crystal, Cognos), automating ETL and scripts, supporting end users, and monitoring clinical quality measures (NCQA/HEDIS).

Lead product strategy and roadmap for enterprise marketing data products (MDP, Customer 360, conversational analytics). Coordinate data engineering delivery, design scalable data models, improve data governance and quality, modernize cloud-native architectures, and enable AI-ready customer intelligence to support measurement, personalization, and commercial decision-making.

Design and lead implementation of an enterprise Lakehouse: define end-to-end architecture, data pipelines, modeling, governance, MDM, and data quality. Lead discovery with stakeholders, align solutions to business needs, and drive adoption and roadmap delivery.

Design, build, and optimize HANA-native data models and analytical objects for S/4HANA, BW/4HANA, and standalone HANA. Translate business requirements into performant calculation views, CDS views, AMDPs, and SQLScript. Diagnose and resolve HANA performance issues, handle replication, security models, and support migrations/upgrades as needed.

Designs and executes end-to-end data migrations into SAP S/4HANA, including extraction, transformation, validation, reconciliation, and cutover. Partners with functional teams, business owners, and infrastructure stakeholders to ensure data integrity, compliance, and successful system transitions. Provides troubleshooting, documentation, and migration governance.

Design, build, and operate large-scale Hadoop-based data processing pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support enterprise analytics, ML, and reporting. Ensure reliable, performant production systems, troubleshoot issues, and document solutions.