Bixal

Data Engineer

Remote Data Engineering role with clear candidate location fit.

PostedJul 5, 2026

Eligible countries1 accepted country

Seniority signalSenior

Work settingRemote

Accepted candidate locations

USA

AWS CI/CD Python Spark SQL

Role overview

Data Engineer

Requirements and responsibilities

Readable role content extracted into sections for faster review.

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.

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.