Senior Data Engineer

Luxoft; London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading technology company in London is seeking a Senior Data Engineer. You will architect and maintain data pipelines using Python, PySpark, and AWS EMR, ensuring data quality and integrity. The role involves collaboration with cross-functional teams and mentoring junior engineers. Strong experience in Snowflake and data governance is required. Competitive compensation and growth opportunities available.

Qualifications

• 5+ years of experience in data engineering or software development.
• Strong proficiency in Python and PySpark.
• Hands-on experience with AWS services.
• Deep understanding of Snowflake architecture.
• Solid grasp of data modeling and SQL optimization.

Responsibilities

• Build and maintain scalable ETL pipelines.
• Develop and optimize distributed data workflows.
• Design and implement Snowflake data warehouses.
• Partner with teams to deliver reliable datasets.
• Enforce data security and governance standards.

Skills

Python

PySpark

AWS EMR

Snowflake

SQL optimization

CI/CD

Data governance

Collaboration

Tools

Terraform

CloudFormation

Git

Job description

Overview

Project description

We're seeking a highly skilled and motivated Senior Data Engineer to join our growing data team. In this role, you'll architect and maintain robust, scalable data pipelines and infrastructure that power our analytics, machine learning, and business intelligence initiatives. You'll work with cutting-edge technologies like Python, PySpark, AWS EMR, and Snowflake, and collaborate across teams to ensure data is clean, reliable, and actionable.

Responsibilities

• Build and maintain scalable ETL pipelines using Python and PySpark to support data ingestion, transformation, and integration.
• Develop and optimize distributed data workflows on AWS EMR for high-performance processing of large datasets.
• Design, implement, and tune Snowflake data warehouses to support analytical workloads and reporting needs.
• Partner with data scientists, analysts, and product teams to deliver reliable, well-documented datasets.
• Ensure data integrity, consistency, and accuracy across multiple sources and systems.
• Automate data workflows and processes to improve efficiency and reduce manual intervention.
• Monitor pipeline performance, identify bottlenecks, and resolve issues proactively.
• Apply best practices in CI/CD, version control (e.g., Git), and infrastructure-as-code (e.g., Terraform, CloudFormation).
• Enforce data security, compliance, and governance standards in line with industry regulations.
• Mentor junior engineers, conduct code reviews, and foster a culture of continuous learning and knowledge-sharing.

Skills

Must have

• 5+ years of experience in data engineering or software development.
• Strong proficiency in Python and PySpark.
• Hands-on experience with AWS services, especially EMR, S3, Lambda, and Glue.
• Deep understanding of Snowflake architecture and performance tuning.
• Solid grasp of data modeling, warehousing concepts, and SQL optimization.
• Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions) and infrastructure-as-code.
• Experience with data governance frameworks and security best practices.
• Excellent communication and collaboration skills.

Nice to have

N/A