Data Engineer III

JPMorgan Chase

Quick summary

Work type: On-site
Location: London, United Kingdom
Posted: 4 days ago
Nearby: 58 roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $165k

$118k most similar roles pay here $211k

This listing doesn't post a salary. Most similar roles pay $126,800–$202,300.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 368 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 198 roles with salary data.

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At a glance

TL;DR · Data Engineer III

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As a Data Engineer III at JPMorgan Chase within the Personal Investing team, you will build and maintain scalable data platforms and pipelines that support analytics and regulatory reporting for over 275,000 UK investors. Your daily tasks include developing robust cloud-native solutions using Python, PySpark, and dbt to ensure reliable data processing and quality. You’ll also manage batch and streaming data pipelines with Apache Airflow, optimize data models, and implement infrastructure-as-code practices with Terraform. Additionally, you will containerize services with Docker and Kubernetes, contribute to the software development lifecycle, and collaborate in an agile environment to deliver high-quality outcomes. This role requires hands-on experience with cloud technologies like AWS or Azure, SQL-based workflow management tools such as dbt, and messaging systems like Kafka.

Skills

Python PySpark dbt Apache Airflow Terraform Docker Kubernetes AWS SQL Airflow Kafka CI/CD Spark Trino Helm

What you'll do

Build and maintain scalable data processing frameworks using Python, PySpark, and dbt.
Develop and manage batch and streaming data pipelines with Apache Airflow for reliability.
Implement and optimize data models and warehouse structures to support analytics workloads.
Write clean, testable Python/PySpark code following object-oriented principles and unit testing.
Containerize and deploy services using Docker, Kubernetes, and Helm for cloud-native applications.

What we're looking for

At least 5 years of hands-on professional experience as a data engineer
Experience with major cloud technologies (AWS, Google Cloud, Azure)
Proficiency in Python using object-oriented programming and unit testing
Hands-on experience with SQL and dbt for workflow management
Familiarity with infrastructure-as-code tools like Terraform
Understanding of messaging/streaming systems such as Kafka or Pub/Sub
Experience with data orchestration tools like Apache Airflow

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