Job Description:As a Sr. Data Engineer, you will design, build, and support scalable data solutions that enable faster, more reliable decision-making across engineering, test lab, and product development operations. You will partner with cross-functional teams to transform raw data into trusted, governed, analytics-ready data products through modern data pipelines, cloud platforms, data modeling, and data quality practices.
Duties and Responsibilities
- aDesign, develop, and maintain scalable data pipelines, data models, and data integration solutions that support engineering and test operations.
- Build reliable ETL/ELT processes to ingest, transform, validate, and deliver data from multiple source systems into analytics-ready environments.
- Partner with engineering, lab operations, IT, analytics, and business stakeholders to understand data needs and translate them into technical solutions.
- Establish and maintain data quality checks, validation rules, and monitoring processes to ensure trusted and accurate data.
- Develop and optimize data warehouses, data lakes, and cloud-based data platforms for performance, reliability, and scalability.
- Create reusable data assets, curated datasets, and documentation that enable self-service reporting, analytics, and operational visibility.
- Collaborate with software developers and IT teams on secure data architecture, system integrations, source control, deployment, and development best practices.
- Translate business strategy and operational needs into technical data solutions that improve efficiency, quality, and speed of decision-making.
- Monitor pipeline performance, troubleshoot production issues, and proactively improve data reliability, observability, and maintainability.
- Mentor team members on data engineering standards, coding practices, documentation, and data governance principles.
- Adhere to timelines and excel in a fast-paced, high-energy environment while balancing technical excellence with practical business impact.
Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, or a related technical field; equivalent experience may be considered.
- 5+ years of experience in data engineering, software engineering, analytics engineering, or related technical roles.
- Strong proficiency in SQL and at least one programming language such as Python, C#, Java, or Scala.
- Experience designing and supporting ETL/ELT pipelines, data warehouses, data lakes, relational databases, and cloud-based data platforms.
- Experience working in cloud environments such as Azure or AWS, including data storage, compute, orchestration, and security concepts.
- Working knowledge of data modeling, database design, data integration patterns, APIs, and scalable system architecture.
- Familiarity with modern data engineering tools and practices such as Spark, Databricks, Airflow, dbt, Fabric, or automated testing.
- Strong understanding of data quality, data governance, data security, documentation, and operational monitoring practices.
- Ability to understand complex business processes, create process maps, and translate operational workflows into data solutions.
- Strong analytical, problem-solving, and communication skills with the ability to influence technical decisions across cross-functional teams.
