Top Data & Analytics Jobs

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.

Work with stakeholders to build and maintain integrations, data pipelines, dashboards, and internal tools. Gather requirements, document workflows and sources, support rollout/configuration, and troubleshoot internal applications to surface operational data across engineering, supply chain, finance, and operations.

Lead Tilt's Business Intelligence function end-to-end: manage a distributed BI team, own reporting data models and semantic layer, build and maintain a metric-and-metadata library with reference SQL, review dbt work and hold quality through code review, prioritize stakeholder requests, and grow team technical and business fluency.

Lead ETL/Data Warehouse architect designing and optimizing Snowflake DWHs, building ETL with Informatica (IICS/PowerCenter/IDMC), guiding teams, producing architecture and technical documentation, managing projects, and presenting complex information to business and technical stakeholders. Works with pharma life-science datasets (IQVIA, Komodo, Veeva).

Design, build, and support enterprise data platforms, semantic/ontology models, and scalable data pipelines. Implement data quality, lineage, metadata, CI/CD, governance (including RLS), and observability. Provide technical leadership, mentor team members, and collaborate with stakeholders to enable analytics, AI, and LLM-driven solutions.

Lead and grow a data engineering team to build a trusted, fast, composable, and self-serve data platform. Define architecture and roadmap for ingestion, transformation, governance, and analytics; ensure reliability, observability, and security; partner cross-functionally with Product, Analytics, Security, and Engineering; be a hands-on player-coach delivering scalable data systems using Snowflake, dbt, and self-serve analytics.