Databricks Engineer

Robotics Technologies; Austin (TX); On-site; USD 130,000 - 170,000; Full time

Job summary

Robotics Technologies LLC is seeking a Databricks Engineer to design and optimize scalable data pipelines on the Databricks Lakehouse Platform. You will transform large datasets, implement ETL/ELT workflows, and ensure governance and security across enterprise analytics initiatives.

The role requires strong Python, PySpark, and SQL skills, plus hands-on Spark and Delta Lake experience. Collaboration with data teams and clean, reliable data processing are key focus areas.

Qualifications

• 5+ years of data engineering or big data development experience.
• 3+ years hands-on Databricks and Apache Spark experience.
• Strong programming in Python, PySpark, and SQL.
• Understanding distributed computing, data architecture, and performance tuning.
• Experience with cloud storage and data governance concepts.

Responsibilities

• Design, develop, and optimize scalable data pipelines on the Databricks Lakehouse Platform.
• Build ETL/ELT workflows for structured and unstructured data.
• Implement data transformation and validation using Spark SQL and Python.
• Manage Delta Lake tables and optimize storage and performance.
• Configure and maintain Databricks clusters, jobs, and workflows.
• Collaborate with data architects, analysts, and business teams to enable analytics.

Skills

Databricks Lakehouse

Python

PySpark

SQL

Apache Spark

Delta Lake

Delta Live Tables

Databricks Workflows

Unity Catalog

Data governance

Airflow

CI/CD

Education

Bachelor's degree in CS/IT/Data Engineering

Master's degree preferred

Databricks Data Engineer Associate

Databricks Data Engineer Professional

Tools

Azure Databricks

AWS Databricks

Databricks on Google Cloud

Delta Live Tables

ADLS / Amazon S3 / GCS

Git

CI/CD pipelines

Azure Data Factory

Databricks Workflows

Job description

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

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Position Overview:

The Databricks Engineer will design, develop, and optimize scalable data engineering solutions using the Databricks Lakehouse Platform. This role focuses on building robust data pipelines, processing large datasets, implementing data transformation workflows, and supporting enterprise analytics initiatives.

Technical Skills & Platform Expertise:

Strong hands-on experience with Databricks and the Lakehouse architecture.

Proficiency in Python, PySpark, and SQL for large-scale data processing.

Experience with Apache Spark, Spark SQL, and Delta Lake.

Knowledge of data ingestion, ETL/ELT pipelines, and data transformation frameworks.

Experience with Azure Databricks, AWS Databricks, or Databricks on Google Cloud.

Familiarity with cloud storage services such as ADLS, Amazon S3, and Google Cloud Storage.

Experience with Delta Live Tables, Workflows, Unity Catalog, and Databricks SQL.

Knowledge of data modeling, dimensional modeling, and data warehousing concepts.

Familiarity with orchestration tools such as Apache Airflow, Azure Data Factory, or Databricks Workflows.

Experience with Git, CI/CD pipelines, and automated deployment practices.

Understanding of data governance, access controls, security, and performance optimization.

Develop and maintain scalable data pipelines using Databricks and PySpark.

Build ETL/ELT workflows to process structured and unstructured data.

Implement data transformation and validation using Spark SQL and Python.

Design and manage Delta Lake tables and optimize data storage.

Configure and maintain Databricks clusters, jobs, and workflows.

Integrate data from multiple sources into centralized lakehouse environments.

Optimize Spark workloads, query execution, and cluster performance.

Implement data quality checks, monitoring, and error-handling mechanisms.

Apply Unity Catalog and governance standards to secure enterprise data.

Collaborate with data architects, analysts, and business teams to deliver analytics solutions.

Experience & Professional Capabilities:

5+ years of experience in data engineering or big data development.

3+ years of hands-on experience with Databricks and Apache Spark.

Strong programming experience with Python, PySpark, and SQL.

Understanding of distributed computing, data architecture, and performance tuning.

Strong analytical, debugging, and problem-solving skills.

Educational Background & Certifications:

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field.

Master's degree is preferred.

Databricks certifications such as Data Engineer Associate or Data Engineer Professional are an advantage.

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.