Data Engineer III - Python, Databricks

Build secure, scalable data pipelines and analytics foundations using Python and Databricks in an onsite Houston environment.

• Develop workflows and ELT pipelines using Python and Databricks
  .
• Support review of controls to ensure sufficient protection of enterprise data
  .
• Implement data security using entitlements frameworks
  .
• Update logical or physical data models as new use cases emerge.
• Use SQL frequently and apply working knowledge of No
  
  SQL databases
  .
• Apply enterprise-authorized AI capabilities within the work environment to accelerate data pipeline and design analysis/documentation.
• Validate AI-assisted outputs and handle data according to sensitivity and security requirements
  .
• Use reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (including test generation and control validation
  ).
• Ensure traceability/auditability and alignment to resiliency and security expectations.

• Formal training or certification on software engineering concepts and 3 years of applied experience.
• Good working knowledge of AWS
  , Databricks
  , and Python
  , with experience across the data lifecycle.
• Advanced SQL skills, including joins and aggregations
  ; working understanding of No
  
  SQL databases.
• Significant experience with statistical data analysis and the ability to select appropriate tools and data patterns.
• Ability to utilize AWS Cloud Services to develop, deploy, and manage applications at scale.
• Proficiency with AI coding assistants
  , using tools daily such as Cursor
  , Git Hub Copilot
  , and Claude for code generation, documentation, and refactoring.
• Prompt engineering skills: provide context, clear goals, relevant source material, and defined output expectations to produce accurate, usable code.
• Critical evaluation and validation to identify hallucination patterns, security vulnerabilities, and logic errors in AI-generated code before production deployment.
• Demonstrated experience using enterprise-authorized AI capabilities to support data engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (query suggestions, test ideas, model change summaries) before use;
  escalate when uncertain and follow data handling requirements.

• Familiarity with Standardized data layer practices, including Medallion architecture
  .
• Exposure to Aurora Postgres and MongoDB
  .
• Experience developing and supporting AWS GLUE Jobs and Federated Data Lake
  .
• Skills in designing efficient data models, including normalization
  , denormalization
  , and schema design
  , with understanding of relational and star schemas
  .
• Augmented development workflow: integrating tools into CI/CD pipelines, using containerization (for example,
  Docker
  ), and leveraging AI to bridge language gaps (for example, transitioning between Python
  , Java Script , or Java
  ).

• Python, Databricks, ELT, SQL, No
  
  SQL
• AWS, AWS GLUE Jobs, Federated Data Lake, Aurora Postgres
• Medallion architecture
• Cursor, Git Hub Copilot, Claude
• Docker, CI/CD
• MongoDB, Federated Data Lake
• JavaScript, Java

• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching

Location: Houston, TX (onsite)

Minimum Experience: 3 years