Top Data & Analytics Jobs

Leads a 20+ person Analytics Engineering organization responsible for revenue, bookings, people analytics, and go-to-market data pipelines. Sets technical strategy, drives data transformation and governance, owns internal analytics agents and semantic layers, advances AI-assisted engineering, and partners with Product, Engineering, GTM, and business stakeholders. The role also supports customer conversations, thought leadership, cross-functional roadmaps, and enterprise-scale data initiatives.

Performs data quality assurance for large datasets by validating imports, updates, transformations, and extracts. Writes SQL test queries, reviews database logic, executes test cases, identifies defects, verifies corrections, and documents testing results. Collaborates with data engineers, business analysts, project managers, and QA professionals to ensure data integrity and compliance with requirements.

Build and operate scalable Python-first ETL and ELT pipelines for genomic and operational data. Integrate LIMS, laboratory instruments, applications, and third-party sources while guiding architecture and engineering standards. Own data quality, lineage, observability, reproducibility, audit readiness, security, and regulatory compliance across hybrid and cloud environments. Work with SQL databases, workflow orchestration, containers, Kubernetes, AWS data services, distributed processing, streaming, bioinformatics workflows, and infrastructure as code.

Designs and supports enterprise data integrations, ETL/ELT pipelines, APIs, data models, and transformations across Microsoft platforms. Maintains data quality, governance, security, and reliability while developing CI/CD pipelines, deployment automation, and release processes. Troubleshoots integration and deployment issues, manages environments, supports reporting and analytics, and collaborates with technical and business stakeholders to deliver scalable data solutions.

Leads business analysis for insurance underwriting technology solutions, including requirements elicitation, process analysis, user stories, stakeholder alignment, testing, UAT, traceability, and production support. Partners with underwriters, product managers, developers, and QA teams across policy, claims, billing, and underwriting initiatives. Drives process improvements and uses Microsoft Copilot to enhance requirements documentation, impact analysis, and delivery efficiency.

Build and manage high-volume analytics and production ETL/ELT systems. Partner with Data Science, Engineering, and Product teams to ensure reliable Search data logging and usage. Own data quality, observability, security, compliance, SLAs, scalability, performance, and cost efficiency across the data lifecycle. The role requires expertise in Python, SQL, data modeling, distributed data technologies, massive datasets, and data pipeline optimization.

Administers and optimizes the HRIS, including configuration, upgrades, integrations, troubleshooting, and data governance. Develops standard and ad hoc reports, KPI dashboards, regulatory reports, and employee survey outputs. Analyzes workforce data to identify trends, recommend improvements, and support strategic decisions. Partners with vendors and IT on system enhancements while ensuring data integrity, privacy, and operational efficiency.

Build and operate analytics pipelines, data models, data marts, and quality systems for mobile free-to-play game telemetry. Maintain and optimize BigQuery transformation layers, migrate Airflow pipelines to a partner-managed ETL platform, define tracking plans and data contracts, and develop observability capabilities. Partner with studios and analysts to support retention, monetization, and engagement reporting while applying production engineering, documentation, and collaboration practices.

Design and operate end-to-end infrastructure for intracortical neural data, from ingestion and validation through preprocessing, versioned dataset releases, and training data loaders. Preserve scientific metadata and provenance while implementing signal processing, quality checks, storage optimization, parallel processing, and monitoring. Collaborate with neuroscience, machine learning, infrastructure, and IT teams to support scalable, reliable model training and sensitive research-data management.

Manages and prepares data from internal and external sources, validates data quality, performs descriptive, predictive, and prescriptive analysis, and documents methodologies and outcomes. Develops and maintains self-service reporting tools and dashboards, supports regular and ad hoc reporting, trains customers, and presents audience-appropriate findings. Identifies anomalies, investigates root causes, ensures reproducibility, and provides recommendations to support data-driven underwriting and actuarial decisions.