We are seeking a highly skilled Lead Data Engineer with proven experience in Databricks and AWS to join our data engineering team.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology Finance team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Architect, develop, and optimize large-scale data pipelines and analytics platforms, leveraging Databricks (Spark, Delta Lake) and AWS cloud services
• Lead a team of data engineers, collaborate with data scientists and business stakeholders, and ensure best practices in data engineering, security, and cloud architecture
• Design, build, and maintain scalable ETL/ELT data pipelines using Databricks (Spark, Delta Lake) on AWS
• Architect and implement data lake and data warehouse solutions leveraging AWS services (S3, Glue, Redshift, Lambda, EMR, etc.)
• Lead and mentor a team of data engineers, providing technical guidance and code reviews
• Optimize data workflows for performance, reliability, and cost efficiency
• Collaborate with data scientists, analysts, and business teams to deliver high-quality data products
• Ensure data quality, security, and compliance with organizational and regulatory standards
• Drive adoption of best practices in data modeling, version control, CI/CD, and infrastructure-as-code (e.g., Terraform, CloudFormation)
• Troubleshoot and resolve issues in production data pipelines and analytics platforms

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• 10+ years of experience in data engineering
• Deep hands-on experience with Databricks (Spark, Delta Lake, notebooks, job orchestration)
• Strong expertise in AWS data ecosystem (S3, Glue, Lambda, IAM, etc.)
• Proficient in Python and/or Scala for data engineering
• Experience with SQL, data modeling, and performance tuning
• Familiarity with CI/CD, DevOps, and infrastructure-as-code in cloud environments
• Excellent communication and leadership skills
• Proven leadership experience in leading and mentoring varying levels of software engineers
  Preferred qualifications, capabilities, and skills- Experience with data governance, security, and compliance frameworks
• Experience with Immuta and Data quality control systems