Databricks Engineer

Robotic Technologies Automation; Austin (TX); On-site; USD 84,000 - 120,000; Full time

Job summary

Robotic Technologies Automation seeks a Databricks Engineer to augment the data platform team in Austin. You will design and implement robust lakehouse pipelines, catalogued datasets, and enterprise data products while aligning with Unity Catalog governance and architecture.

The role requires adapting to new domains and collaborating with internal leads. The ideal candidate has 5+ years in data engineering, with 2+ years on Databricks in cloud environments, strong PySpark/SQL skills, and

Qualifications

• Bachelor's degree in Computer Science, Information Systems, or related field preferred.
• 5+ years of data engineering experience, including 2+ years with Databricks in a cloud environment.
• Proficiency in Python (PySpark and pandas), SQL, Delta Lake, and Unity Catalog; Git and CI/CD experience required.

Responsibilities

• Design and build production data pipelines on Databricks with PySpark, SQL, Delta Lake, Unity Catalog, and Jobs.
• Define bronze/silver/gold data layers, data contracts, schemas, SLAs, and quality checks.
• Develop ML-oriented data products including feature stores, embeddings for RAG, and batch inference.
• Integrate pipelines with cloud services using key vaults, managed identities, and private connectivity.
• Expose stable APIs, tables, and volumes powering orchestration workflows with ML teams.
• Document data dictionaries and runbooks; participate in code reviews and agile ceremonies.

Skills

Data engineering

Python programming

SQL proficiency

Education

Bachelor's degree in CS or related field

Tools

Databricks

Delta Lake

Unity Catalog

Git

CI/CD

Pandas

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: Databricks Engineer
Location: Austin, TX
Duration: 9 Months + Extension
Bill Rate: $74/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Summary

An established organization is seeking a skilled professional to augment the internal data platform team. This role focuses on delivering robust lakehouse pipelines, catalogued engineering datasets, and enterprise data products in parallel with ongoing priority programs. The ideal candidate will quickly adapt to new domains, collaborate closely with internal leads, and contribute to standardizing Unity Catalog governance and architecture.

Key Responsibilities

• Design and build production data pipelines on Databricks utilizing PySpark, SQL, Delta Lake, Unity Catalog, and Workflows/Jobs with high standards for monitoring and clear lineage.


• Model bronze, silver, and gold layers alongside defining data contracts, schemas, service level agreements, and quality checks.


• Develop machine learning-oriented data products, including feature stores, curated tables, embedding generation, chunking and indexing for RAG, and batch classification.


• Integrate data pipelines with cloud services, utilizing security patterns such as key vaults, managed identities, and private connectivity.


• Partner with application and machine learning teams to expose stable APIs, tables, and volumes that power orchestration workflows.


• Document data dictionaries, runbooks, and handoff materials while actively participating in code reviews and agile ceremonies.

Required Qualifications

Education: Bachelor's degree in Computer Science, Information Systems, or a related technical field is preferred.

Experience: Minimum of 5 years of experience in data engineering, including at least 2 years of production experience with Databricks in a cloud environment.

Technical Skills: Proficiency in Python (PySpark and pandas), SQL, Delta Lake, and Unity Catalog. Practical experience with Git, continuous integration repository layouts, and unit testing for data pipelines is required.

Preferred Qualifications

• Experience building pipelines that feed machine learning and generative AI use cases, such as vector search inputs and batch inference outputs.


• Proven ability to work effectively within staff augmentation models alongside internal technology leads.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.