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# Software Engineer [Multiple Positions...

- **Company:** JPMorgan Chase & Co.
- **Location:** Jersey City, NJ, United States
- **Experience:** Experienced
- **Salary:** $164,400.0 - $185,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Data Analysis, Systems Engineering, CA Workload Automation Ae, Behavior-Driven Development, Big Data, Cloud Computing, Cloud Database, Computer Clusters, Databases, Computer Engineering, Continuous Integration, Data Integrity, Extract Transform Load (ETL), Data Mining, Serialization, Data Structures, Data Vault Modeling, Dimensional Modeling, Distributed Computing Environment, Distributed Systems, Amazon DynamoDB, Apache Hadoop, JSON, Python (Programming Language), PostgreSQL, Unix Shell, Machine Learning, MySQL, NoSQL, Open Database Connectivity, Workflow Management Systems, Parquet, Qliksense, Data Processing, Data Storage Technologies, Feature Engineering, Delivery Pipeline, Snowflake, Apache Spark, Information Technology, Apache Flink, Cassandra, Avro, AWS Glue, AWS Data Analytics, Non-relational Database, Data Pipelines, Databricks
- **Published:** July 16, 2026
- **Apply:** https://www.juju.com/job/00000000ggwabu

## About the Role

REQUIREMENTS: Master's degree in Information Technology and Management, Computer Science, Computer Engineering, or related field of study plus 3 years (36 months) of experience in the job offered or as Software Engineer, Software Developer, Systems Engineer, or related occupation. The employer will alternatively accept a Bachelor's degree in Information Technology and Management, Computer Science, Computer Engineering, or related field of studyplus 5 years (60 months) of experience in the job offered or as Software Engineer, Software Developer, Systems Engineer, or related occupation This position requires three (3) years of experience with the following: Performing exploratory data analysis on large-scale enterprise databases to identify trends, anomalies, and opportunities for data extraction, cleaning, transformation, and loading; Applying linear algebra, statistics, and geometrical algorithms to analyze and interpret datasets, enhancing data preprocessing and feature
engineering for machine learning models; Managing and optimizing relational and NoSQL databases, including Postgres, MySQL, Cassandra, and DynamoDB for high performance, scalability, and reliability; Implementing and monitoring backup, recovery, and archiving strategies to safeguard data integrity and ensure availability in case of failures or disasters; Designing, developing, and automating end-to-end data workflows and cloud-based pipelines to enable seamless data movement, transformation, and integration across platforms and applications using ETL processes, ODBC connectors, and orchestration tools such as Airflow, Autosys, AWS Step Functions, DBT, or AWS Glue; Building and maintaining scalable data processing pipelines to handle large volumes of data using cluster computing frameworks including Spark, Flink, and Storm and cloud-native solutions; Optimizing data storage, retrieval, and interoperability using big- data formats such as Parquet or Iceberg and serialization
formats including JSON and AVRO; Designing and managing cloud-based data lakehouse platforms using AWS Data Lake, Databricks, Hadoop, and Snowflake; Developing dynamic dashboards and visualizations using ThoughtSpot and Qlik Sense to communicate insights to stakeholders, enabling business users to create visualizations through drag-and-drop interfaces, and automating dashboard updates and recurring reports; Coding with Python, Java, or Scala for data processing, transformation, and automation; Developing Unix shell scripts to support data manipulation and workflow automation across distributed environments; Designing scalable, high-performance data structures for analytics and reporting using data modeling techniques such as dimensional modeling, Data Vault, Kimball, or Inmon, including conformed dimensions, fact tables, and normalized models; Optimizing models using indexing, partitioning, and appropriate normalization or denormalization strategies; Aligning with business

## Description

DUTIES: Manage and optimize relational and non-relational databases, implementing strategies for backup, recovery, and archiving. Perform exploratory data analysis to extract, clean, transform, and load data from large enterprise systems. Implement and maintain cloud-based data pipelines to support scalable and reliable workflows. Develop and maintain dynamic, interactive dashboards and automate recurring reports. Utilize distributed computing frameworks for large-scale data processing. Manage big-data storage and serialization formats and automate workflows using scheduling and orchestration frameworks. Apply dimensional and enterprise data modeling techniques, and implement batch, micro-batch, and stream-based data processing methodologies. Develop program increment plans and roadmaps and implement test-driven or behavior-driven development with continuous integration and delivery pipelines. Manage infrastructure using declarative configuration and provisioning techniques.
Coach team members on design and development best practices and promote continuous improvement in product quality and team capabilities.


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