Top Data & Analytics Jobs

Staff Data Engineer leading architecture and technical direction for real-time and batch motorsports data platforms. Responsibilities include telemetry ingestion, streaming systems, data quality, observability, cloud platforms, reliability, incident response, technical standards, roadmap planning, stakeholder influence, and mentoring. The role delivers scalable solutions supporting race-day operations and cross-functional analytical products.

Leads Motorsports Data Infrastructure and Data Science teams while owning the strategy, architecture, and delivery of data platforms supporting telemetry, simulation, trackside, analytics, and AI/ML use cases. Responsibilities include managing managers, designing streaming and batch pipelines, productionizing ML models, setting engineering standards, managing Azure and Databricks capacity, protecting sensitive data, and partnering with racing and executive stakeholders. The role remains hands-on in architecture, coding, code review, incident support, and technical problem-solving.

Analyzes connected-vehicle customer journeys, system performance, operational workflows, and production incidents. Builds dashboards and reports, writes SQL queries, investigates root causes, detects trends and anomalies, and translates findings into corrective actions. Partners with engineering and contact-center teams to resolve customer-impacting issues, improve connected-service reliability, define metrics, validate changes, and establish scalable operational practices.

Design, build, and optimize scalable batch and streaming data pipelines using Fivetran, Databricks, Spark, Azure, Kafka, and Kubernetes. Develop source integrations, improve data delivery and infrastructure scalability, monitor and troubleshoot production workloads, and ensure SLA compliance. Contribute to architecture and technology decisions, automate deployments and monitoring, collaborate across teams, and mentor junior engineers supporting intelligent manufacturing analytics.

Design and optimize scalable cloud data warehouses, data lakes, pipelines, and Operational Data Stores for near-real-time IoT analytics. Integrate and process large datasets using Databricks, Snowflake, Flink, Spark, Kubernetes, and Iceberg. Monitor pipeline health, improve performance and cost efficiency, ensure data quality and security, and collaborate with technical and business stakeholders.

Leads consumer research for GM International markets, managing quantitative and qualitative studies from design through analysis and recommendations. Combines survey, behavioral, digital, CRM, social, market, and secondary data to generate actionable insights for product, marketing, communications, technology, and local strategy decisions. Develops research instruments, oversees suppliers, manages complex stakeholders and timelines, creates executive presentations, and applies AI-enabled research methods responsibly.

Design and productionize scalable batch and streaming data pipelines and governed data products in Azure Databricks. Build lakehouse architectures, automation, AI-enabled retrieval and semantic workflows, and production data solutions supporting analytics, ML, LLMs, and agents. Establish standards for testing, quality, lineage, observability, security, and cost management while solving complex engineering problems. Partner with data science and ML teams, influence technical direction, mentor engineers, and improve delivery practices.

Develop data models and automated solutions supporting semiconductor supply chain mapping, resiliency, distribution operations, and supply forecasting. Perform exploratory and targeted analyses, preprocess structured data, monitor model effectiveness, and present insights through data visualization. Collaborate with technical teams and stakeholders on cross-functional projects, communicate data-driven recommendations, and manage ambiguous business problems independently. The role requires domestic and international travel of less than 25% and follows a hybrid work schedule.

Design, build, and operate scalable real-time and batch data pipelines ingesting high-frequency telemetry, simulation, and trackside data. Own Kafka/Flink streaming components, Databricks lakehouse implementations, and infrastructure-as-code deployments. Develop software in Python/Java/SQL, integrate systems, automate testing and releases, performance-tune pipelines, and mentor peers to ensure resilient, secure, high-performance data delivery for motorsports teams.

Build, scale, and operate an enterprise telemetry data platform that ingests, processes, and publishes vehicle telemetry at global scale. Develop batch and streaming pipelines using Databricks and Spark, implement observability and data quality controls, optimize distributed workloads for performance and cost, and enable reliable production data products through CI/CD and Infrastructure as Code. Provide technical leadership and partner with analytics, AI, and engineering teams.