Databricks Engineer

Quantum Technologies. LLC; Austin (TX); In loco; USD 120.000 - 190.000; Tempo pieno

Descrizione del lavoro

Quantum Technologies. LLC in Austin, TX, seeks a Databricks Engineer to design, build, and optimize scalable data pipelines on the Databricks Lakehouse Platform, enabling enterprise analytics and data-driven decisions.

You will work with Python, PySpark, SQL, Spark, and Delta Lake to ingest data, transform workflows, and ensure governance, security, and performance. Collaboration with data architects, analysts, and business teams is essential.

Competenze

• 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.

Mansioni

• Design, develop, and optimize scalable data pipelines on Databricks Lakehouse Platform.
• Process large datasets and implement data transformation workflows.
• Collaborate with data architects, analysts, and business teams to deliver analytics solutions.
• Ensure data governance, access controls, security, and performance optimization.
• Implement data quality checks, monitoring, and error-handling mechanisms.

Conoscenze

Databricks Lakehouse

Python

PySpark

SQL

Apache Spark

Delta Lake

Data ingestion

ETL/ELT pipelines

Git / CI/CD

Data governance

Formazione

Bachelor’s degree in CS/IT/Data Engineering

Master’s degree preferred

Databricks Data Engineer certification advantageous

Strumenti

Databricks

Apache Spark

Airflow

Azure Data Factory

Delta Lake

Unity Catalog

Descrizione del lavoro

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.