Top Data & Analytics Jobs

The BI ETL Data Developer II/III develops and maintains scalable data pipelines in a cloud-based environment, enhancing data integrity and quality for informed decision-making across the University.

As a Sr Data Engineer, you'll conduct feasibility analyses, develop applications, monitor processes, consult with users, and ensure compliance while serving as a mentor to junior analysts.

Build and operate real-time and batch data pipelines for maritime domain awareness. Parse binary sensor and SONAR data, design high-performance data warehouses, validate and normalize sources, and improve local development and CI/CD. Work on-site with customers, write production-quality code, and integrate systems to support mission-critical deployments.

As a Data Engineer, you'll create and maintain data pipelines, optimize data architecture, and support analytics tools for performance insights.

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

Develop and maintain data infrastructure for safety data analysis, build scalable data pipelines, conduct exploratory analyses, and support regulatory reporting in AV safety.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The role involves SQL and data analysis to troubleshoot issues, with 8+ years of required experience. Experience with C# and scripting tools is preferred.

Design and build Starlink's commercial operating system by identifying go-to-market bottlenecks, architecting scalable systems and AI-powered workflows, integrating CRM and data platforms, improving commercial data quality, and enabling data-driven decision-making to drive revenue and operational efficiency.

Design, implement, and optimize scalable data pipelines and infrastructure on AWS. Maintain ETL artifacts, provide Tier 3 support, collaborate with stakeholders and a product team, document dataflows, and occasionally support off-hours deployments.

The data engineer will build and maintain data pipelines, implement data models, write quality checks, configure tooling, and resolve pipeline issues.

As a Snowflake Data Engineer, you will design and maintain scalable data pipelines, optimize SQL transformations, and support analytics platforms, collaborating with stakeholders.

This role offers training for aspiring Data Engineers, focusing on technology of choice, interview preparation, and skill enhancement with guidance on OPT STEM extension.

Design and maintain scalable ETL/ELT pipelines, data integrations, APIs, databases, warehouses, and workflow orchestration. Improve data quality, security, governance, reporting accessibility, and infrastructure reliability across a multi-location organization. Collaborate with analysts, technology teams, and business leaders, troubleshoot complex data issues, support CI/CD deployments, and provide technical leadership and mentorship while shaping long-term data strategy.

Lead design and implementation of enterprise-scale data architectures, pipelines, and integration frameworks supporting ontologies, knowledge graphs, and Semantic Web technologies. Build and optimize ETL/ELT processes for structured and unstructured data, enable cloud/containerized deployments, ensure data quality, lineage, governance, and support AI/ML initiatives. Provide technical leadership, documentation, automated monitoring, and mentorship to Government stakeholders and project teams.

Design and build scalable pipelines and evaluation frameworks to compute driving-performance metrics across fleet and simulation data. Perform deep analysis of time-series, event, and geospatial data to identify regressions and root causes. Build geospatial analytics, release gating tooling, and LLM-powered agentic workflows to triage issues and propose fixes. Collaborate with engineering teams and adhere to QMS processes.

Design, build, and maintain scalable data ingestion pipelines into BigQuery; replace legacy ETL/ELT; implement orchestration (Airflow/Dagster/Prefect); support DBT and CI/CD; tune BigQuery performance; set up monitoring/alerting; maintain documentation and data governance.

Support building and testing digital solutions for production lines: analyze operational workload, assist with big data analytics and prototypes, troubleshoot production/maintenance tasks, and communicate insights under mentorship.

The Lead Data Engineer will design and build data architectures, lead a team, and develop ETL processes using cloud technologies to optimize data solutions for the U.S. business.

Design and maintain scalable data pipelines, models, curated datasets, analytics solutions, and manufacturing automation tools. Support Ignition and Sepasoft MES systems, integrate manufacturing software, and develop solutions for metrology and image inspection data. Apply software engineering practices and independently lead complex cross-functional projects from requirements through deployment.

Build and maintain scalable data pipelines, analytics data warehouses, ETL processes, data models, and infrastructure supporting reporting, analytics, and machine learning. Ensure data quality from creation through presentation layers, translate stakeholder needs into deliverables, improve tooling and pipeline reliability, and participate in on-call support. The role involves modern big data architecture, containerization, cloud platforms, and data engineering technologies.

Design, build, and maintain data structures, ETL/ELT pipelines, and data products. Support operational data processes, performance tuning, data governance, documentation, and stakeholder collaboration. Mentor junior staff and improve data platform quality and accessibility.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Build and enhance Databricks-based platform capabilities and reusable data products for quantitative researchers and analysts. Develop and operate pipelines integrating heterogeneous data sources, while improving governance, automation, observability, security, and operational excellence. Define target-state platform architecture, evaluate emerging technologies, and use infrastructure as code, CI/CD, Apache Airflow, and AI-assisted development tools to accelerate prototypes into production.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, quality frameworks, governance, observability, and self-service analytics practices. Partners with stakeholders, leads technical reviews, mentors engineers, supports hiring, oversees analyses, and participates in incident response and continuous improvement.