As a Lead Software Engineer, you will design and implement scalable data pipelines using Python and PySpark on AWS, manage a team of data engineers, collaborate with stakeholders, ensure data quality, and continuously improve technical solutions.
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 the Asset and Wealth Management, 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
- Lead the design, development, and implementation of scalable data pipelines and ETL batches using Python/PySpark on AWS.
- Execute standard software solutions, design, development, and technical troubleshooting
- Use infrastructure as code to build applications to orchestrate and monitor data pipelines, create and manage on-demand compute resources on cloud programmatically, create frameworks to ingest and distribute data at scale.
- Add to team culture of diversity, equity, inclusion, and respect.
- Manage and mentor a team of data engineers, providing guidance and support to ensure successful product delivery and support.
- Collaborate proactively with stakeholders, users and technology teams to understand business/technical requirements and translate them into technical solutions.
- Optimize and maintain data infrastructure on cloud platform, ensuring scalability, reliability, and performance.
- Implement data governance and best practices to ensure data quality and compliance with organizational standards.
- Monitor and troubleshoot application and data pipelines, identifying and resolving issues in a timely manner.
- Stay up-to-date with emerging technologies and industry trends to drive innovation and continuous improvement.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Demonstrable hands-on experience in Python and PySpark.
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- Proven experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Good understanding of data modeling, data architecture, ETL processes, and data warehousing concepts.
- Experience with big data technologies and services like AWS EMRs, Redshift, Lambda, S3.
- Excellent communication skills to work effectively with stakeholders, partner teams, and to translate technical concepts into business terms.
- Proven experience with efficient Cloud DevOps practices and CI/CD tools like Jenkins/Gitlab, for data engineering platforms.
- Good knowledge of SQL and NoSQL databases, including performance tuning and optimization.
- Strong analytical skills to troubleshoot issues and optimize data processes, working independently and collaboratively.
- Experience in leading and managing a team of engineers, with a proven track record of successful project delivery.
Preferred qualifications, capabilities, and skills
- Knowledge of machine learning concepts, language models and cloud-native MLOps pipelines and frameworks is a big plus.
- AWS Certifications in data engineering and machine learning is a plus.
- Familiarity with data visualization tools and data integrations.
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