Lead Data Engineer - Cloud, Databricks
Join 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 Lead Cloud Data Engineer at JPMorgan Chase within Employee Experience Employee Core Data Platform(Palmos) Group, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job 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
- Adds to team culture of diversity, equity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on data engineering concepts and 5+ years applied experience
- At least 5 years of recent hands-on professional experience (actively coding) working as a data engineer
- Hands-on experience with Apache Kafka, Spark Experience in using Databricks for big data analytics and processing.
- Hands-on practical experience in system design, application development, testing, and operational stability, particularly data pipelines for moving/transforming data.
- Experience and proficiency across the data lifecycle. Overall knowledge of the Software Development Life Cycle
- Experience with SQL and understanding of NoSQL databases and their niche in the marketplace
- Experience designing and implementing data pipelines in a cloud environment is required.
- Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
- Hands on experience in building applications using AWS services like Lambda, EMR and EKS, REST API. Strong experience migrating/developing data solutions in the AWS cloud is required. Experience needed in AWS Services, Apache Airflow.
- Experience with database back-up, recovery, and archiving strategy
- Proficient knowledge of linear algebra, statistics, and geometrical algorithms
Preferred qualifications, capabilities, and skills
- 1+ years of experience building/implementing data pipelines using Databricks such as Unity Catalog, Databricks workflow, Databricks Live Table etc.
- AWS Data Platform experience
- Experience with Data Orchestrator tool like Airflow.
- Familiarity with data governance and metadata management.
- Spark programming and advanced at SQL (e.g., joins and aggregations)
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