Top Data & Analytics Jobs

Lead and mentor a data engineering team to architect and implement scalable cloud lakehouse/warehouse solutions, design enterprise data models, build batch and real-time ETL/ELT pipelines, enforce data quality and governance, establish CI/CD and DataOps practices, and enable AI and advanced analytics.

Leads Pacsun’s enterprise business intelligence, data warehouse, analytics, and system integration strategy. Oversees BI developers and analysts, MuleSoft integrations, retail systems including Microsoft D365 and Manhattan OMS/POS, ETL and OLAP initiatives, data architecture, modeling, validation, and AI-driven predictive analytics. Partners with business and IT leaders on ERP and financial system transformation, resolves technical challenges, documents data designs, and mentors the BI team.

Manage Filevine’s corporate analytics function, including executive dashboards, KPI reporting, data pipelines, and complex analyses. Lead and mentor data analysts, ensure data integrity, track SaaS metrics such as ARR, GRR, NRR, churn, and retention, and translate insights into strategic recommendations. Partner with executive leadership and Finance, Operations, Product, and Customer Success teams to support business decisions.

Lead a team of 10+ data engineers while remaining hands-on in architecture, design, and code. Own a unified ingestion framework, Spark streaming pipelines, Apache Iceberg lakehouse, dbt modeling standards, Trino query performance, reliability SLOs, observability, cost optimization, and 24x7 on-call operations. Partner cross-functionally on roadmap decisions and build scalable, standardized data platform infrastructure with strong incident-management practices.

Administer and optimize SQL Server, AWS Aurora, PostgreSQL, and related database environments supporting DOL SWARAS reporting. Responsibilities include performance tuning, backup and recovery, replication, data integrity, reporting support, incident troubleshooting, Tier 2/3 support, database security, vulnerability remediation, audit readiness, and technical documentation. The role requires federal database administration experience, prior DOL IT program experience, U.S. citizenship, and eligibility for DOL Public Trust suitability.

Build and maintain reliable enterprise data platform automation and integrations across Cognite Data Fusion, Databricks, Azure, streaming services, and enterprise systems. Monitor platform health, pipelines, alerts, and data refreshes; troubleshoot incidents; support deployments, migrations, provisioning, and validation. Implement security, IAM, governance, data quality, backup, and disaster recovery practices. Develop reusable workflows, contextualize data products, maintain runbooks, and collaborate with architects, engineers, product teams, and vendors.

Research, annotate and structure financial data from public filings using proprietary tools; standardize and maintain databases, ensure data integrity, collaborate on reporting requirements, and support special projects. Role requires attention to detail, ability to handle high-volume quarterly periods (overtime eligible), and strong Excel skills.

Leads and develops a data engineering team implementing data integrations for partner campuses. Owns implementation approaches, scalable delivery processes, data mapping, validation, reconciliation, quality controls, project health, and capacity planning. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve integrations, and support adoption. Provides technical mentorship, design and code reviews, stakeholder communication, and continuous process improvement.

Lead company-wide data and analytics strategy across insurance and real estate investment operations. Build governance, collection frameworks, reporting platforms, dashboards, models, and KPI systems; translate complex data into executive insights; automate analytics workflows; support underwriting, claims, forecasting, capital allocation, and portfolio performance; and build and mentor a high-performing analytics team while remaining hands-on.

Build and scale data pipelines supporting Vehicle Configuration Optimization. Ingest and transform Snowflake data into Databricks using Bronze, Silver, and Gold medallion layers. Develop Python and SQL ETL/ELT workflows, monitor pipeline health, optimize performance, and implement data quality and governance controls. Partner with data scientists, analysts, and stakeholders to produce curated datasets for analytics, simulation, and machine learning.