Data Engineer

Bixal

Data Engineer at Bixal optimizing data pipelines with PySpark and AWS. Collaborating with cross-functional teams for effective data engineering solutions.

Posted 7/3/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $130,000 - $135,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Data Engineering with a focus on designing and implementing data ingestion pipelines using PySpark and Databricks. Proficient in AWS services, data pipeline optimization, and leading cross-functional technical initiatives.

Highest-signal resume keywords

Data Engineering ExpertisePySpark DevelopmentDatabricks Intelligence PlatformAWS Services (S3, IAM)Technical SME Leadership

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Python ProgrammingData Pipeline DesignSQL Query AuthoringData Transformation TechniquesData ModelingData Storage OptimizationRoot Cause AnalysisVersion Control (Git)Infrastructure as Code (Terraform)Linux Environment Management

Soft Skills

Problem-SolvingCollaborationAttention to DetailVerbal CommunicationWritten Communication

Tools & Technologies

Databricks NotebooksLakeflow JobsUnity CatalogDelta ShareCI/CD Processes

Certifications & Qualifications

Public Trust Security Clearance

Industry Keywords

Data Ingestion PipelinesStreaming ArchitecturesEnterprise Architecture StandardsTechnical DocumentationAgile Projects

Tech Stack

Tools & technologies

AWSKafkaLinuxPySparkPythonSQLTerraformUnity

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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