Senior Data Engineer

Bold Thinking. World Changing. At SkyWater, our ingenuity helps improve lives around the world by manufacturing U.S. made semiconductors that are essential ingredients of modern life. Automotive safety enhancements, life-saving medical devices, consumer electronics and American security require semiconductors. Working in our Minnesota headquarters or Florida location, employees join together to improve the world.


Explore what’s possible. Joining our U.S. - based team means contributing to and learning about the commercialization of some of the most exciting technologies the world has ever seen. We are turning “science fiction” into everyday reality through technologies such as superconducting, 3D integrated circuits or computer chips, carbon nanotubes, photonic logic devices, micro electro-mechanical systems and other emerging device topologies. We manufacture products for aerospace and defense, medical, automotive, consumer and industrial markets, to name a few. Our customers include emerging leaders who rely on our intellectual property security and quality manufacturing services.


Step into the future. SkyWater’s values of Integrity, Excellence, Collaboration, Empowerment and Growth Mindset guide us to cultivate an empowered, learning environment. We also invest in developing highly skilled, dedicated employees — and employees who are entering the workforce for the first time, from the military, and a variety of educational backgrounds.


Are you bold thinking? Find your place on our team and help us change the world!


**US Citizenship Required: This position will require the holding of or ability to obtain government security clearance which requires U.S Citizenship.
We are looking for a highly skilled and experienced Senior Data Engineer to join our growing Data, Analytics, and AI team. In this role, you will be responsible for designing, building, and optimizing scalable data pipelines and systems to support analytics, machine learning, and business intelligence initiatives. You will work closely with analysts and engineering teams to ensure high data quality, availability, and performance.
Key Responsibilities
· Design, implement, and maintain scalable and efficient data pipelines using modern data stack tools (e.g., Airflow, dbt, Spark).
· Develop ETL/ELT processes to ingest data from a variety of structured and unstructured sources (APIs, databases, third-party systems).
· Work across domains to gather requirements, architect, and build new/novels solutions to support the appropriate business requirements.
· Work with business stakeholders to develop/build reporting dashboards.
· Optimize performance of BI solutions.
· Collaborate with architects, engineers, and analysts to design and optimize data models for analytics and operational use.
· Ensure data quality and integrity through robust testing, monitoring, and documentation practices.
· Optimize performance of databases and data workflows to support real-time and batch processing.
· Mentor junior engineers and contribute to team development and best practices.
· Work across teams to identify, support, and troubleshoot as needed.
· Work with stakeholders to understand data needs and deliver data solutions that drive business insights.
· Implement data governance practices, including data security, privacy, and compliance.
Qualifications
· Master’s degree in Computer Science, Engineering, Information Systems, or a related field with 5+ years of experience in data engineering, with a strong focus on building and maintaining data infrastructure at scale OR Bachelors degree with at least 10+ years of experience.
· Proficient in Python, SQL, and one or more big data technologies (e.g., Spark, Hadoop, Kafka).
· Experience with managing cloud IAM permissions, data access controls, and key management.
· Experience with cloud data platforms such as AWS (Redshift, S3, Glue), GCP (BigQuery, Dataflow), or Azure.
· Hands-on experience with orchestration tools like Airflow or Prefect.
· Experience with infrastructure-as-code (Terraform, CloudFormation) and CI/CD practices is a plus.
· Strong understanding of data modeling, warehousing concepts, and distributed systems.
· Knowledge of BI tools such as Tableau, Power BI, or QlikView.
· Excellent problem-solving, communication, and collaboration skills.
Preferred Qualifications
· Experience with dbt for data transformation and version control.
· Strong background with Dev-Ops and ML-Ops
· Familiarity with containerization (Docker, Kubernetes).
· Knowledge of data privacy regulations (e.g., GDPR, HIPAA, FEDRAMP) and security best practices.
· Experience with both batch and streaming data pipelines.
· Experience within semiconductor manufacturing.


The annual salary range for this role is $153,440 - $230,160. Pay offered is bas