Senior Data Engineer, Data Management & BI

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer, Data Management & BI based in United States. This role focuses on designing and supporting scalable data solutions that enable trusted analytics, operational reporting, and data-driven decision-making. You will build reliable data pipelines, models, integrations, and cloud-based processing solutions across structured and semi-structured data sources. The position combines hands-on engineering with architecture, automation, data quality, observability, and production support. You will work closely with product, analytics, engineering, and business stakeholders to turn complex or ambiguous requirements into dependable technical solutions. The role also provides opportunities to influence engineering standards, mentor other engineers, and improve how data is delivered and governed. You will operate in a fast-moving environment where performance, reliability, testing, documentation, and operational readiness are critical. This is a fully remote opportunity offering broad exposure to modern cloud data platforms, BI technologies, distributed processing, and emerging AI-assisted engineering practices. Accountabilities: - 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 supporting analytics and operational workflows. - Develop reusable and maintainable code using modern data engineering practices, with a strong focus on performance, testability, observability, reliability, and long-term supportability. - Build and optimize batch, event-driven, and serverless data-processing solutions using cloud-native services and distributed processing frameworks.

- Contribute to architecture decisions covering data lakes, data warehouses, orchestration, metadata, APIs, and application integration patterns. - Implement data quality controls, monitoring, alerting, and operational runbooks to ensure production pipelines remain accurate, reliable, and supportable. - Design and maintain CI/CD pipelines, automated testing, deployment workflows, and infrastructure-as-code practices that accelerate delivery while reducing operational risk. - Partner with analytics, BI, product, and business teams to deliver trusted, timely, 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 to simplify data flows. - Participate in Agile delivery activities including sprint planning, backlog refinement, code reviews, release planning, incident response, and retrospectives. - Mentor engineers and promote strong engineering practices across code quality, documentation, testing, production readiness, and operational support. - Create and maintain technical documentation, architecture diagrams, data lineage information, implementation guides, and support materials as platforms and systems evolve. Requirements - Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Analytics, or a related field, or equivalent practical experience. - 5+ years of hands-on data engineering experience designing, building, testing, deploying, and supporting production data pipelines. - Strong knowledge of data modeling, data architecture, ETL/ELT patterns, metadata, data quality, and data warehouse or data lake methodologies. - Hands-on experience with cloud data engineering services such as AWS S3, Lambda, Athena, EMR or EMR Serverless, Glue, Step Functions, SNS, SQS, or comparable technologies.