About the role:

We are seeking a skilled and motivated Data Engineer to join our dynamic team as we continue to build and optimize data pipelines using PySpark, Databricks, AWS, and other cutting-edge technologies. The successful candidate will bring expertise in PySpark, Databricks, AWS, Kafka/streaming architectures, and infrastructure as code (IaC), and will be responsible for platform reliability, scalability, and evolution across the program.

This is a full-time position supporting a current contract. This role offers you a unique opportunity to make a meaningful impact on a project that aligns with Bixal's mission of delivering innovative, human-centered solutions. While the role has a fixed duration, we are committed to transparency and collaboration, keeping you informed about contract updates and new opportunities. At Bixal, we support your professional journey, ensuring your experience reflects our inclusive, purpose-driven culture and prepares you for future success.

Location

This role can work remotely from anywhere in the USA. Applicants must be authorized to work for any employer in the U.S. Bixal does not sponsor employment visas or assume sponsorship of existing employment visas.
Compensation:

The salary range for this role is $95,000 - $115,000. In the spirit of transparency, most offers tend to land near the midpoint of the range. We make compensation decisions thoughtfully, considering your experience, the skills you bring, and our commitment to internal equity. Fairness and transparency are core to how we operate.

Responsibilities:

• Leading the implementation of complex data ingestion pipelines using PySpark, Databricks Intelligence Platform, and AWS services (S3, IAM roles and policies), including Kafka/streaming architectures, schema evolution, and Delta Share, ensuring alignment with enterprise architecture standards.
• Provide technical guidance and mentorship to engineers across the team and representing data engineering in cross-functional discussions.
• Apply engineering standards, including code quality, testing practices, CI/CD processes, and infrastructure as code patterns using Terraform.
• Author and maintain architectural documentation, technical decision records, and platform runbooks that enable team autonomy and operational excellence.
• Guide and implement optimization opportunities across data ingestion, transformation, and storage layers.
• Troubleshoot complex pipeline failures across multi-system dependencies.
• Collaborate with data scientists, analysts, DevOps engineers, and client teams to deliver integrated solutions that meet program objectives.
• Other relevant duties as qualified and trained to perform

Qualifications:

• Bachelor's degree.
• Minimum of 4 years of relevant experience in Data Engineering.
• Demonstrated experience working cross-functional engineering initiatives.
• Proficiency in Python for data engineering tasks at scale.
• Hands-on experience with Databricks Intelligence Platform (Notebooks, Lakeflow Jobs, Unity Catalog, Delta Share)
• Experience with AWS services such as S3 and IAM roles and policies.
• Strong knowledge of data pipeline design and implementation, including data transformation techniques, data modeling, data storage optimization, and data security best practices.
• Proficiency in using version control systems like Git for managing code repositories and collaborating with team members on Agile projects.
• Familiarity with Terraform or other infrastructure as code tools for automating infrastructure deployment and configuration management.
• Experience working on Linux environments for data engineering projects, including accessing containers remotely, installing packages, managing files, services, and processes.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong problem-solving skills, ability to work independently and as part of a team, and excellent verbal and written communication skills.
• Comfortable working in a highly collaborative environment with strong attention to detail and a commitment to delivering high-quality software.
• Ability to obtain and maintain a Public Trust security clearance.

Nice to Have Skills and Experience:

• Experience working with other data frameworks such as Apache Hive, Apache Hadoop, or Apache Spark is a plus.
• Federal consulting experience
• Databricks certifications (Associate Data Engineer or Professional Data Engineer).
• Experience with business intelligence tools (e.g., QuickSight, Power BI) for building data observability or usage reporting.

How We Support Our Team:

• Flex hours
• 401K with matching incentive
• Parental Leave
• Medical/dental/vision benefits
• Flex Spending Account
• Company provided short-term disability and life insurance
• Commuter benefits
• Paid Time Off (PTO)
• 11 Paid holidays

Department Client Delivery Role AI & Data Engineering Locations Remote within United States Remote status Fully Remote