Data Engineer

Job Description

Job Description

Important Notice for Applicants:
At Bixal, we want to ensure a transparent and secure application process for all candidates. Official communication will come from an email address ending in @bixal.com or from @bixal.na.teamtailor -mail.com. Messages from other sources may be fraudulent, and you should exercise care to avoid any links or attachments included.

Bixal will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Need Assistance or a Reasonable Accommodation?
If you need assistance or a reasonable accommodation to complete your application, we're here to help. Please reach out to us at View email address on ziprecruiter.com and let us know how we can support you. You do not need to share personal details or disclose the nature of your request. You can expect a response from a team member within 24 hours during the regular work week and on the next operating day during the weekend or holidays.

Why Bixal?

Bixal is a consulting company headquartered in Fairfax, VA, working alongside governments and organizations to help them deliver better services and experiences to the communities they serve. Using evidence-based knowledge and technology, Bixal empowers clients to deliver on their missions more effectively by fostering a culture of learning and continuous improvement.

Our values:

• People-First : Emphasizing the importance of people in all aspects of work.

• Collaboration and Transparency : Valuing teamwork and open communication.

• Growth Mindset : Encouraging innovation and continuous improvement.

• Creating Lasting Impact : Focusing on meaningful outcomes and positive change.

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 deep expertise in PySpark, Databricks, AWS, Kafka/streaming architectures, and infrastructure as code, 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., be able to obtain and maintain the required Public Trust clearance, and obtain a U.S. Federal Government client badge, which requires demonstrated U.S. residency for 3 of the last 5 years. Bixal does not sponsor employment visas or assume sponsorship of existing employment visas.

Compensation:

The salary range for this role is $130,000 – $135,000. 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:

• Lead the design and 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.

• Serve as a subject matter expert (SME) for data engineering, providing technical guidance and mentorship to engineers across the team and representing data engineering in cross-functional discussions.

• Take ownership of platform reliability and performance, proactively identifying optimization opportunities across data ingestion, transformation, and storage layers. Troubleshoot complex pipeline failures across multi-system dependencies.

• Lead cross-functional technical initiatives, collaborating with data scientists, analysts, DevOps engineers, client teams (upstream data providers and downstream consumers), and stakeholders to deliver integrated solutions that meet program objectives.

• Contribute to the data platform technical vision and architecture, making strategic decisions on tooling, frameworks, and design patterns that shape the program's long-term data engineering direction.

• Define and enforce engineering standards, including code quality, testing practices, CI/CD processes, and infrastructure as code patterns using Terraform.

• Evaluation of new technologies and approaches, presenting proof of concepts and technical roadmaps to leadership.

• Author and maintain architectural documentation, technical decision records, and platform runbooks that enable team autonomy and operational excellence.

• Other relevant duties as assigned and qualified/trained to perform

Qualifications:

• Bachelor’s degree.

• Minimum of 5 years of experience in Data Engineering.

• Demonstrated experience serving as a technical SME and leading cross-functional engineering initiatives.

• Proficiency in Python for data engineering tasks at scale.

• Deep expertise with Databricks Intelligence Platform (Notebooks, Lakeflow Jobs, Unity Catalog, Delta Share) and the ability to define platform standards and best practices for the team.

• 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:

• Bachelor’s degree in a technology field.

• Familiarity with cloud computing concepts, particularly as they apply to data engineering, is a plus.

• 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

Our company is committed to providing equal employment opportunities for all individuals and complies with all applicable federal, state, and local anti-discrimination laws. Employment decisions are based on merit, qualifications, and business needs.