Software Engineer III - Data Engineer
JPMorgan Chase & Co.Match Score
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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and operate scalable ETL/ELT data engineering pipelines and data products on AWS using Databricks, Spark, and lakehouse architecture.
Lead adoption and integration of AI-assisted engineering practices (GitHub Copilot, Claude) across the ETL lifecycle ensuring security and human oversight.
Develop and maintain infrastructure as code, CI/CD pipelines, orchestration workflows (Airflow), and implement disciplined engineering practices including monitoring, testing, and governance.
Minimum Requirements
8 years of hands-on data engineering or software engineering experience delivering production data platforms and pipelines.
Strong experience with Databricks, Spark, Delta Lake, and lakehouse architectures on AWS.
Proficiency in Python, PySpark, SQL; experience with AWS Glue, Airflow (or equivalent), and Apache NiFi for ingestion and workflow orchestration.
Experience with infrastructure as code (Terraform and/or AWS CloudFormation), automated testing, secure coding, data governance, and AI-assisted workflows with controls for PII/PCI data.
Ideal Candidate Profile
Senior data engineer with expertise in modern data platforms, cloud-native ETL patterns, and disciplined DevOps practices in AWS environments.
Experience leading AI-assisted data engineering tools integration and adoption across the development lifecycle with strong security and compliance focus.
Candidates with knowledge of agentic automation, data mesh concepts, metadata management, plus mentoring and standards leadership experience.