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# Data Engineer

- **Company:** BCforward
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $160,160.0 - $172,640.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Agile Methodology, Airflow, Amazon Web Services, Code Review, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Distributed Systems, Online Banking, Operational Databases, SQL Databases, Enterprise Data Management, Data Processing, Data Ingestion, Snowflake, Apache Spark, Data Lakes, Pyspark, Low Latency, Enterprise Integration, Data Management, Data Pipelines, Control M
- **Published:** July 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=25d8f29f67c3788a

## About the Role

* 5+ years of Data Engineering experience.
 * Strong ETL development experience.
 * Hands-on experience with Apache Spark / PySpark.
 * Snowflake Data Warehouse.
 * Apache Airflow.
 * AWS Cloud Services.
 * Data Lake experience.
 * Java Spark or PySpark.
 * SQL and data transformation.
 * Experience building enterprise-scale data pipelines.
 * Agile/Scrum development experience.

Preferred Skills

 * Control-M
 * High-volume, low-latency distributed systems
 * Banking or Financial Services experience
 * AWS Certification, * data engineer: 7 years (Required)
 * AWS: 5 years (Required)
 * Spark: 4 years (Required)
 * ETL: 4 years (Required)

## Description

Client is seeking experienced Data Engineers to join a high-impact team building next-generation banking platforms.

The team is responsible for developing scalable data pipelines that support Open Banking capabilities, enabling secure integration between Chase accounts and external financial institutions. This is a hands-on engineering role focused on building enterprise-grade data platforms, modernizing data pipelines, and processing large-scale financial datasets.

Responsibilities

 * Design, develop, and maintain scalable ETL/data pipelines for enterprise data platforms.
 * Build and optimize data ingestion and transformation processes using Spark and PySpark.
 * Develop and manage data workflows using Airflow and Control-M.
 * Build and maintain Snowflake data warehouse solutions.
 * Develop high-performance data processing applications using Java Spark or PySpark.
 * Integrate data from multiple internal and external sources into enterprise data lakes.
 * Optimize data pipelines for scalability, reliability, and performance.
 * Work closely with software engineers, product owners, and business stakeholders in an Agile environment.
 * Troubleshoot production data pipeline issues and implement long-term solutions.
 * Participate in code reviews and follow engineering best practices.


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