Role : Sr. Data Engineer

Location: Pasadena, CA

Work Arrangement: Hybrid

Job Summary

We are looking for an experienced Data Engineer with strong expertise in Databricks, PySpark, and Python to design, develop, and maintain scalable data engineering solutions. The ideal candidate will have hands-on experience building ETL/ELT pipelines, data processing frameworks, and data lake/lakehouse solutions using Databricks and cloud technologies.

Key Responsibilities

Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and Python.
Develop ETL/ELT workflows to ingest, transform, cleanse, and integrate data from multiple sources.
Build and optimize data processing jobs using PySpark and Spark SQL.
Work extensively with Databricks Lakehouse, Delta Lake, notebooks, workflows, and clusters.
Develop reusable Python modules and frameworks for data processing and automation.
Implement data quality checks, validation, error handling, and monitoring within data pipelines.
Optimize Spark jobs, including partitioning, caching, joins, and performance tuning.
Work with Delta Lake for data storage, transformation, versioning, and incremental processing.
Integrate data from relational databases, APIs, files, cloud storage, and other enterprise data sources.
Collaborate with Data Architects, Data Scientists, BI Developers, and business stakeholders to understand data requirements.
Implement CI/CD and source-control practices for data engineering code.
Troubleshoot production data pipeline failures and perform root cause analysis (RCA).
Ensure data security, governance, lineage, and compliance requirements are followed.
Participate in design discussions, code reviews, testing, deployment, and production support.

Required Skills

Strong hands-on experience with Databricks
Strong PySpark / Apache Spark experience
Strong Python programming skills
Experience developing ETL/ELT pipelines
Strong SQL skills
Experience with Delta Lake
Experience with data lake/lakehouse architecture
Experience with Spark performance tuning and optimization
Experience working with large-volume datasets
Strong understanding of data modeling and data engineering concepts
Experience with Git and CI/CD
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform

Preferred Skills

Databricks certification
Experience with Azure Data Factory / AWS Glue / Airflow
Experience with Azure Data Lake / Amazon S3
Experience with Unity Catalog
Experience with Kafka or other streaming technologies
Experience with Terraform
Experience with data governance and data quality frameworks
Experience with Power BI, Tableau, or other BI platforms

Typical Technology Stack

Sr. Data Engineer

Key skills

About this role