About the Role
We are seeking an experienced ETL Developer (Lead Data Engineer) to join the Enterprise Information Warehouse team. This role focuses on building scalable data integration solutions and supporting the organization's migration to Google Cloud Platform (GCP). The ideal candidate has extensive experience with Ab Initio, Spark, cloud technologies, and enterprise data warehousing.
Key Responsibilities
Design, develop, test, and deploy enterprise ETL processes.
Build and optimize scalable data pipelines using Ab Initio, Spark, Airflow, and BigQuery.
Support migration of enterprise data workloads to Google Cloud Platform.
Develop and maintain data warehouse solutions for reporting and analytics.
Review code and improve application performance and reliability.
Troubleshoot production issues and optimize data processing.
Collaborate with business stakeholders and engineering teams in Agile/Scrum.
Participate in architecture discussions and technical design reviews.

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
6+ years of Data Engineering experience.
6+ years of Ab Initio development.
Strong Spark experience (Spark Core, Spark SQL, DataFrames, Datasets).
Experience with Google Cloud Platform (BigQuery, Airflow, SparkFlow).
Python scripting experience.
Strong SQL skills with Teradata, Oracle, and PL/SQL.
Data Warehouse design and ETL development.
Hadoop, Hive, Autosys.
Distributed systems and parallel processing.
Agile/Scrum development experience.
Strong communication skills.
Nice to Have Skills & Experience
Team Lead or Technical Lead experience.
Kafka and MongoDB.
Machine Learning pipelines.
Vertex AI.
LLMs and Agentic AI frameworks.
Apache Spark ML.
Sparkling Water / H2O.
Unix Shell Scripting.
CI/CD pipelines.
Infrastructure as Code.
Cloud deployment automation.

ETL Developer

Similar Engineering Jobs