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 AI/ML & Data Platform 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
- Design, develop, and maintain ETL processes (using Python, AWS) to support data integration and data warehousing solutions.
- Collaborate with data architects, data analysts, and business stakeholders to understand data requirements and translate them into technical specifications.
- Optimize and tune ETL processes (using Python, AWS) for performance and scalability.
- Ensure data quality and integrity through rigorous testing and validation procedures.
- Monitor and troubleshoot ETL processes to resolve issues and ensure timely data availability.
- Develop and maintain documentation for ETL processes, data flows, and data models.
- Mentor and provide guidance to junior ETL engineers and data team members..
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Practical experience in ETL development using Python and AWS, with a focus on data engineering.
- Proficient in debugging, optimization, and understanding various data formats (CSV, Parquet, ORC) and sources (HDFS, S3, SFTP, Apache Iceberg).
- Expertise in the Software Development Life Cycle and advanced knowledge of agile methodologies, including CI/CD, application resiliency, and security.
- Familiarity with programming languages such as Java or Scala.
- Experience with cloud platforms like AWS, Azure, or GCP and their data services
Preferred qualifications, capabilities, and skills
- Familiar with big data technologies (e.g., Hadoop).
- Preferred experience with Apache Spark and strong SQL skills for relational databases like Oracle, SQL Server, and MySQL.
- Data governance and data security best practices.
- Familiar with real-time data processing and streaming technologies (e.g., Kafka, Flink).
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