Databricks Data Engineer

KINETIQ; Irvine (CA); On-site; USD 115,000 - 125,000; Full time

Job summary

KINETIQ is seeking three Databricks-certified Data Engineers to build and maintain data pipelines on the Databricks Lakehouse Platform. You will work onsite alongside senior engineers, analysts, and business stakeholders to deliver reliable, well-structured data for reporting and analytics.

Responsibilities include developing ETL/ELT pipelines, ingesting data from multiple sources, and implementing a Medallion Architecture. Strong Python/SQL skills and Databricks experience are required.

Qualifications

• 2–5 years of data engineering experience with hands-on Databricks project work.
• Strong Python and SQL skills; working knowledge of Apache Spark.
• Experience with at least one cloud platform (Azure, AWS, or GCP).
• Understanding of data modeling and data warehousing fundamentals.

Responsibilities

• Develop and maintain ETL/ELT pipelines using Databricks, PySpark, Spark SQL, and Delta Lake.
• Ingest and transform data from multiple sources (databases, APIs, files, cloud storage).
• Work within a Medallion Architecture (Bronze/Silver/Gold).
• Write clean, tested, and reusable Python and SQL code.
• Monitor, troubleshoot, and tune pipeline performance.
• Schedule and orchestrate jobs with Databricks Workflows or similar tools.
• Use Git and team CI/CD practices for version control and deployments.
• Collaborate with analysts and business users to understand data requirements.

Skills

Databricks

Python

SQL

Spark

Cloud platforms

Education

Bachelor's degree in Computer Science, Engineering, or a related field

Tools

Unity Catalog

Delta Live Tables

Auto Loader

Airflow

dbt

Kafka

Event Hubs

Kinesis

Job description

Compensation: $115,000 – $125,000 base salary + benefits

About the Role

We're hiring three Databricks-certified Data Engineers to build and maintain data pipelines on the Databricks Lakehouse Platform. You'll work onsite alongside senior engineers, analysts, and business stakeholders to deliver reliable, well-structured data for reporting and analytics.

Key Responsibilities

• Develop and maintain ETL/ELT pipelines using Databricks, PySpark, Spark SQL, and Delta Lake
• Ingest and transform data from multiple sources (databases, APIs, files, cloud storage)
• Work within a Medallion Architecture (Bronze/Silver/Gold)
• Write clean, tested, and reusable Python and SQL code
• Monitor, troubleshoot, and tune pipeline performance
• Schedule and orchestrate jobs with Databricks Workflows or similar tools
• Use Git and team CI/CD practices for version control and deployments
• Collaborate with analysts and business users to understand data requirements

Required Qualifications

• 2–5 years of data engineering experience, with hands-on Databricks project work
• Strong Python and SQL skills; working knowledge of Apache Spark
• Experience with at least one cloud platform (Azure, AWS, or GCP)
• Understanding of data modeling and data warehousing fundamentals

Preferred Qualifications

• Experience with Unity Catalog, Delta Live Tables, or Auto Loader
• Exposure to streaming data (Kafka, Event Hubs, Kinesis)
• Experience with Airflow, Azure Data Factory, or dbt
• Bachelor's degree in Computer Science, Engineering, or a related field

Work Authorization

Must be authorized to work in the U.S. without sponsorship.