Senior Data Engineer, Data Management & BI

The Senior Data Engineer, Data Mgmt and BI will design, build, and support scalable data solutions that enable trusted analytics, operational reporting, and data-driven decision making across the organization. This role will partner closely with product, analytics, engineering, and business stakeholders to translate ambiguous business needs into reliable technical solutions, while helping establish strong engineering standards across data pipelines, cloud platforms, data models, APIs, automation, and observability. The ideal candidate is a hands-on engineer who can work independently, mentor others, communicate clearly with technical and non-technical partners, and continuously improve how data is delivered, governed, tested, and supported in a fast-moving environment. Design, build, test, deploy, and maintain scalable data pipelines that ingest, transform, validate, and publish structured and semi-structured data from internal and external sources. Translate business and product requirements into technical designs, data models, integration patterns, and execution plans that support reliable analytics and operational workflows. Develop reusable, maintainable code using modern data engineering practices, with an emphasis on performance, testability, observability, and long-term supportability. Build and optimize batch, event-driven, and serverless data processing patterns using cloud-native services and distributed processing frameworks. Contribute to architecture decisions across data lake, warehouse, orchestration, metadata, API, and application integration patterns. Implement data quality checks, monitoring, alerting, and operational runbooks to ensure pipelines are accurate, reliable, and supportable in production. Design and maintain CI/CD pipelines, automated testing, deployment workflows, and infrastructure-as-code patterns that improve delivery speed and reduce operational risk. Partner with analytics, BI, product, and business teams to enable timely, trusted, and well-documented data products and reporting solutions. Evaluate source systems, APIs, files, data contracts, and transformation logic to identify risks, dependencies, data gaps, and opportunities for simplification. Participate in Agile delivery practices including sprint planning, backlog refinement, code reviews, release planning, incident response, and retrospectives. Mentor engineers, promote engineering best practices, and help raise the quality bar for code, documentation, testing, and production readiness. Create and maintain clear technical documentation, architecture diagrams, data lineage notes, implementation guides, and support materials as systems evolve.