Data Engineer - Tech Lead (Databricks, Pyspark)

EPAM Systems; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

ESPP

Private medical insurance

Life assurance

Dental care

Employee Assistance Program

Pension plan

Learning and development

Job summary

EPAM Systems in London is seeking a Senior Data Engineer – Tech Lead to design, develop and optimize cloud-native data architectures with Azure Databricks, PySpark and Lakehouse principles. You will work hands-on to deliver scalable data solutions for high-volume workloads while ensuring governance and reliability.

You will mentor engineers, drive modernization initiatives and shape large-scale data ecosystems.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering or related field.
• Extensive experience designing and implementing production-scale data platforms using Azure Databricks.
• Expertise in PySpark, including optimization and data skew mitigation.
• Strong Python programming skills with modern software design principles.
• Experience with structured streaming, Delta Lake and Delta Live Tables.
• Proven ability to lead Lakehouse migrations using Delta Lake or Apache Iceberg.
• Proficiency with Azure cloud services and multi-cloud knowledge (AWS/GCP).
• Hands-on experience with CI/CD and IaC tools (Terraform, GitHub Actions, Jenkins).
• Strong leadership to guide teams, define epics/user stories, and deliver in agile environments.
• Excellent communication and stakeholder management for technical and non-technical audiences.

Responsibilities

• Lead architecture, design and build of large-scale data platforms using Azure Databricks and cloud technologies.
• Implement and optimize ETL workflows and streaming pipelines with PySpark and Delta Live Tables.
• Enhance performance, control cloud costs and ensure platform reliability for structured streaming.
• Define data governance, security and quality standards across the platform.
• Collaborate with stakeholders to translate business requirements into technical solutions.
• Develop integration approaches using Azure-native services (Data Factory, Synapse, Blob Storage).
• Mentor data engineers and promote modern engineering practices.

Skills

Leadership

Communication

Agile methodologies

Mentoring

Stakeholder management

Education

Bachelor's or Master's degree in Computer Science, Software Engineering or related field

Tools

Azure Databricks

Delta Live Tables

PySpark

Python

Databricks ML/MosaicML

Terraform

GitHub Actions

Job description

We're looking for a Senior Data Engineer – Tech Lead (Databricks, PySpark) to join our team in London, UK, in a hybrid working mode.

In this role, you will lead the design, development and optimization of scalable cloud-native data architectures, focusing on Azure Databricks, PySpark and Lakehouse principles. You will work hands‑on to deliver performant data solutions for high-volume workloads, ensuring governance, reliability and best practices for enterprise-grade platforms.

As a technical leader, you will define data strategies, drive modernization initiatives and mentor engineers, fostering excellence and innovation throughout the team. This position offers the opportunity to shape large-scale data ecosystems, implement modern engineering practices and enable next-generation analytics and AI‑driven solutions.

Responsibilities

• Lead the architecture, design and build of large-scale data platforms using Azure Databricks and modern cloud technologies
• Implement and optimize ETL workflows and streaming pipelines with PySpark and Delta Live Tables following Lakehouse principles
• Enhance performance, manage cloud costs and ensure platform reliability for structured streaming workloads
• Define data governance, security and quality standards to maintain consistency across the platform
• Collaborate with stakeholders to translate complex business requirements into actionable technical solutions
• Develop integration approaches using Azure‑native services such as Data Factory, Synapse and Blob Storage
• Mentor data engineers, promote modern engineering practices and perform technical reviews
• Drive adoption of CI/CD, Infrastructure as Code and automated testing in data engineering environments
• Implement observability and monitoring using tools like Databricks Workflows and related frameworks
• Contribute to AI‑driven initiatives by leveraging Databricks ML/MosaicML to integrate Generative AI and LLM‑based solutions

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering or related field
• Extensive experience designing and implementing production‑grade platforms using Azure Databricks
• Expertise in PySpark, including advanced optimization, data skew mitigation and query tuning
• Strong programming skills in Python with knowledge of modern software design principles
• Practical experience with structured streaming, Delta Lake and Delta Live Tables
• Proven experience in Lakehouse migration and modernization using open table formats such as Delta Lake or Apache Iceberg
• Proficiency with cloud‑native services on Azure and knowledge of multi‑cloud environments (AWS or GCP)
• Hands‑on experience with CI/CD and Infrastructure as Code tools (Terraform, GitHub Actions, Jenkins)
• Strong leadership ability to guide teams, define epics/user stories and ensure delivery in agile environments
• Excellent communication and stakeholder management skills for both technical and non‑technical audiences

Nice to have

• Experience operationalizing LLM or Generative AI workflows in Databricks pipelines
• Familiarity with frameworks like LangChain, LlamaIndex or Databricks ML/MosaicML
• Knowledge of AI governance, security practices and enterprise integration controls
• Background in financial trading data or related domains
• Official Databricks certifications such as Certified Data Engineer Professional or Apache Spark Developer

We offer

• EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in-office, on‑site massages and regular social events
• Learning and development opportunities including in‑house training and coaching, professional certifications, and courses
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program