Databricks AWS Lead Software Engineer

Testing Site - JPMC

Wilmington (DE)

On-site

USD 140,000 - 190,000

Full time

14 days+

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Job summary

JPMorganChase is seeking a Lead Data Engineer with deep Databricks and AWS experience to architect large-scale data pipelines and analytics platforms within the Corporate Technology Finance team.

You will lead a team of data engineers, collaborate with data scientists and business stakeholders, and ensure best practices in data engineering, security, and cloud architecture while driving performance, reliability, and cost efficiency.

Qualifications

  • Formal training or certification on software engineering concepts and 5+ years applied experience.

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.

Skills

Databricks
Spark
Delta Lake
AWS
Python
Scala
SQL
CI/CD
DevOps
Terraform
CloudFormation
Leadership
Data modeling

Education

Software engineering certification

Tools

Terraform
CloudFormation

Job description

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 JPMorganChase within the Corporate Technology Finance team, youare 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
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