DescriptionJoin us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.
As a Lead Data Engineer at JPMorgan Chase within the Corporate Sector and Global Real Estate team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
- Creates secure and high-quality production code.
- Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture.
- Develop & design data pipelines end to end using Spark SQL, Java, and AWS Services. Utilize programming languages like Java, Python, NoSQL databases, SQL, Container Orchestration services, and a variety of AWS tools and services.
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software development concepts and 5+ years applied experience
- Proficiency in designing, developing, testing, debugging, and maintaining code using Java, Scala, Python.
- Hands-on practical experience in developing spark-based Frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark SQL & Spark Streaming.
- Experience with Relational and No SQL databases,
- Cloud implementation experience with AWS including:
- AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Kinesis (or) MSK, Airflow (or) Lambda + Step Functions + Event Bridge
- Data De/Serialization: Expertise in at least 2 of the formats: Parquet, Iceberg, AVRO, JSON-LD
- AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager
- Proficiency in automation and continuous delivery methods.
- Proficient in all aspects of the Software Development Life Cycle.
- Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security.
Preferred qualifications, capabilities, and skills
- Proficiency in multiple modern programming languages
- Advanced knowledge of architecture and solution design across enterprise-scale platforms
