Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code following AWS best practices on cloud systems and responsible to deploy in efficient manner using CICD pipeline.
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies, adds to team culture of diversity, equity, inclusion, and respect
- Participate in scrum team stand-ups, code reviews and other ceremonies, contribute to task completion and blocker resolution within your team
- Handle critical and time sensitive concurrent tasks with supervision and properly escalate situations as appropriate
- Write test cases, leverage unit and integration testing, develop functionality and automation
- Maintain technical acumen by pursuing formal and informal learning opportunities about technology, JPMorgan Chase products, and financial services
- Identify and implement continuous improvement opportunities, to improve delivery flow across product and technology
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- 5+ years of professional work experience designing and implementing data pipelines in a cloud environment is required
- 2+ years of experience migrating/developing data solutions in the AWS cloud is required
- 1+ years of experience building/implementing data pipelines using PySpark on Databricks or similar cloud database
- Expert level knowledge of using SQL to write complex, highly-optimized queries across large volumes of data
- Hands-on object-oriented programming experience using Python is required
- Professional work experience building real-time data streams using Spark and Experience in Spark
- Knowledge or experience in architectural best practices in building data lakes
- Solid understanding of Agile methodologies such as CI/CD, Applicant Resiliency and Security
Preferred qualifications, capabilities, and skills
- Familiarity with Ni-Fi, Snowflake
- Exposure to Terraform and AWS services such as Glue, SQS, SNS,S3 etc