Job Description

JOB DESCRIPTION

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.


As a Lead Software Engineer at JPMorgan Chase within Corporate Technology, you play a vital role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products in a secure, stable, and scalable manner. As a key technical contributor, you are tasked with implementing essential technology solutions across diverse technical domains, supporting various business functions to achieve the firm's strategic goals.

Job responsibilities

Develop appropriate level designs and ensure consensus from peers where necessary. Collaborate with software engineers and cross-functional teams to design and implement deployment strategies using AWS Cloud and Databricks pipelines. Work with software engineers and teams to design, develop, test, and implement solutions within applications. Engage with technical experts, key stakeholders, and team members to resolve complex problems effectively. Understand leadership objectives and proactively address issues before they impact customers. Design, develop, and maintain robust data pipelines to ingest, process, and store large volumes of data from various sources. Implement ETL (Extract, Transform, Load) processes to ensure data quality and integrity using tools like Apache Spark and PySpark. Monitor and optimize the performance of data systems and pipelines. Implement best practices for data storage, retrieval, and processing Maintain comprehensive documentation of data systems, processes, and workflows. Ensure compliance with data governance and security policies

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience Formal training or certification in AWS/Databricks with 10+ years of applied experience. Expertise in programming languages such as Python and PySpark. 10+ years of professional experience in designing and implementing data pipelines in a cloud environment. Proficient in design, architecture, and development using AWS Services, Databricks, Spark, Snowflake, etc. Experience with continuous integration and continuous delivery tools like Jenkins, GitLab, or Terraform. Familiarity with container and container orchestration technologies such as ECS, Kubernetes, and Docker. Ability to troubleshoot common Big Data and Cloud technologies and issues. Practical cloud native experience

Preferred qualifications, capabilities, and skills

5+ years of experience in leading and developing data solutions in the AWS cloud. 10+ years of experience in building, implementing, and managing data pipelines using Databricks on Spark or similar cloud technologies

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