Lead Data Engineer - Databricks
Lead Data Engineer - Databricks
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Job Description
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 a Lead Data Engineer at JPMorgan Chase within the Corporate Technology - FINTECH 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 firms 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-uprecovery and archivingstrategy
- Evaluates and reports onaccesscontrol processes todetermineeffectiveness of dataasset security with minimal supervision
- Adds to team culture of diversity equity inclusion and respect
Required qualifications capabilities and skills
- Formal training or certification on software engineering concepts and 5 years applied experience
- 3 years of experience using technologies such as Databricks Pyspark AWS is essential and creating ETL Pipeline from scratch is a must.
- 3 years of experience working with AWS (Lambda Step Function SQS SNS API Gateway secrets manager and storage services ) is a must.
- 3 years of experience in software engineering and object-oriented programming skills with expertise in Python and Terraform
- Hands on experience with open-source frameworks/libraries such as Apache NiFi Apache Airflow and Autosys.
- Strong understanding of REST API development using FASTAPI or equivalent frameworks.
- Advanced at SQL (e.g. joins and aggregations)
- Familiar with development tools such as Jenkins Jira Git/Stash spinnaker
- Familiarity with unit testing frameworks such as pytest or unittest.
- Extensive experience in statistical data analysis with the ability to select appropriate tools and identify data patterns for effective analysis as well as experience throughout the data lifecycle
Employment Type
Full-Time
