Lead Data Engineer - Databricks
- 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
- 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
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
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