Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

 

As a Data Engineer III at JPMorgan Chase within the Corporate Technology - Global Supply Services team, 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

Implements data solutions to make high-quality data available for analytics and reporting,Collaborates with data analysts, architects, engineers and business stakeholders to understand data requirements.Ensures data quality and consistency by identifying and resolving data issues and creating data reconciliations.Optimizes data workflows and processing for performance, scalability, and reliability.Monitors data pipelines and proactively addresses issues to minimize downtime and disruptions.Documents data engineering processes, data lineage, and data dictionariesStays current with data engineering technologies, best practices, and industry trends.Designs and develops complex data pipelines, ETL (Extract, Transform, Load) processes and decision support systems’ data procedures.Adds to team culture of diversity, equity, inclusion, and respect

 Required qualifications, capabilities, and Skills

Formal training or certification on Data Engineering concepts and 3+ years applied experience.Experience using technologies such as Databricks , Pyspark, AWS, is essential and creating ETL Pipeline from scratch is a must.Experience in working with AWS (Lambda, Step Function, SQS, SNS, API Gateway, secrets manager and storage services ) is a must.Strong software engineering and object-oriented programming skills with expertise in Python and Terraform Familiar with development tools such as Jenkins, Jira, Git/Stash, spinnakerHands 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.Familiarity with unit testing frameworks such as pytest or unittest.Advanced at SQL (e.g., joins and aggregations)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.

Preferred Qualifications, Capabilities, and Skills

Data modeling skills.Familiarity with Kubernetes, Kafka.Experience with containers and container-based deployment environment (Docker, Kubernetes, etc.)Exposure to Oracle Database, Pl/SQL programming & Informatica.