JPMorgan Chase is looking to improve, develop, and provide data collection, storage, access, and analytics solutions that are secure, stable, and scalable within the Consumer & Community Bank- Connected Commerce Technology division.
Requirements
- Experience with both relational and NoSQL databases
- Experience and proficiency across the data lifecycle
- Experience with database back up, recovery, and archiving strategy
- Proficient knowledge of linear algebra, statistics, and geometrical algorithms
- Advanced proficiency in at least one programming language such as Python, Java or Scala
- Advanced proficiency in at least one cluster computing framework such as Spark, Flink or Storm
- Advanced proficiency in at least one cloud data lakehouse platform such as AWS data lake services, Databricks, or Hadoop; at least one relational data store such as Postgres, Oracle or similar; and at least one NOSQL data store such as Cassandra, Dynamo, MongoDB or similar
Responsibilities
- Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms
- Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
- Implements database back-up, recovery, and archiving strategy
- Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
- Develops data strategy and enterprise data models for applications
- Manages data infrastructure including design, construct, install, and maintenance of large scale processing systems and infrastructure
- Drives data quality and ensures data accessibility to analysts and data scientists
Other
- Formal training or certification on data engineering concepts and 5+ years applied experience
- Able to coach team members in continuous improvement of the product and mentors team members on optimal design and development practices
- Adds to team culture of diversity, opportunity, inclusion, and respect
- Ensures compliance with data governance requirements and business alignment including ensuring data engineering practices align with business goals
- Budgeting and resource allocation and vendor relationship management
