Data Engineer — PySpark + AWS Glue

Posted 2 Months Ago
3 Locations
In-Office
Senior level
Information Technology • Consulting • Financial Services
The Role
Design, develop, optimize, and maintain scalable ETL pipelines using PySpark and AWS Glue. Build data ingestion and transformation workflows, orchestrate processes with AWS Step Functions, and develop Python-based AWS Lambda functions. Support AWS data lake architectures, analytical use cases, monitoring, reliability, and performance optimization. The role also involves SQL and may include Java microservices, REST APIs, and backend integrations.
Summary Generated by Built In

Data Engineer — PySpark + AWS Glue

ETL & Data Pipelines | 2 Openings

 

 

Location: Remote (UK)

Employment Type: Contract / Permanent

Experience Level: 4–8 Years

Openings: 2

 

About the Role

We are looking for a skilled Data Engineer with solid hands-on experience in PySpark, AWS Glue, and ETL development to build and maintain scalable, production-grade data pipelines on AWS. You will be part of a delivery-focused team working on complex data engineering challenges, contributing to data lake architecture and end-to-end pipeline development.



Requirements

Key Responsibilities

•       Design, develop, and maintain scalable ETL pipelines using PySpark and AWS Glue

•       Build and optimise data ingestion, transformation, and loading workflows

•       Orchestrate data workflows using AWS Step Functions

•       Develop serverless functions using AWS Lambda (Python)

•       Work with data lake architectures on AWS to support analytical use cases

•       Ensure pipeline reliability, monitoring, and performance optimisation

 

Required Skills & Experience

•       Strong hands-on experience with PySpark and AWS Glue

•       Proven track record in ETL pipeline development and optimisation

•       Experience orchestrating workflows with AWS Step Functions

•       Proficiency in serverless development using AWS Lambda (Python)

•       Good SQL skills and a solid understanding of data processing principles

 

Nice to Have

•       Exposure to Java-based microservices

•       Understanding of REST APIs and backend service integrations

•       Experience working with AWS-based data lakes



Skills Required

  • Strong hands-on experience with PySpark and AWS Glue
  • Proven experience developing and optimizing ETL pipelines
  • Experience orchestrating workflows with AWS Step Functions
  • Proficiency in serverless development using AWS Lambda and Python
  • Good SQL skills and understanding of data processing principles
  • Exposure to Java-based microservices
  • Understanding of REST APIs and backend service integrations
  • Experience working with AWS-based data lakes
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The Company
100 Employees
Year Founded: 2017

What We Do

Yadimen Consulting is a technology consulting firm focused on financial-services organizations. It delivers technology implementation and strategic consulting services, drawing on expertise in data engineering, fraud strategy, data science, enterprise platforms, and product implementation. The company operates across the US, UK, Nordic countries, and Western Europe, helping clients address sector-specific technology challenges and opportunities through tailored solutions for financial institutions and regulated businesses.

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