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Databricks Engineer Jobs

Specialists who build and optimise data pipelines using Databricks. A key role in modern data infrastructure, focusing on scalable and efficient data processing.

Open roles
1
Hiring companies
1
View 1 live role → Get an alert

Databricks Engineers are at the forefront of building and maintaining robust data infrastructure. They work with cutting-edge tools and technologies to create scalable and efficient data pipelines, ensuring that data is processed, stored, and accessed seamlessly. These roles are in high demand across a variety of industries, from finance and healthcare to retail and technology, where data-driven decision-making is crucial. Databricks Engineers collaborate closely with data scientists, data analysts, and other stakeholders to ensure that data infrastructure meets the organisation's needs.

What the role does

Inside the role of a Databricks Engineer

A typical week for a Databricks Engineer is a mix of coding, testing, and collaboration. They spend time writing and optimising Spark jobs, troubleshooting issues, and working with cross-functional teams.

  1. 01
    Design and implement data pipelines using Databricks.
  2. 02
    Optimise and troubleshoot existing data processing workflows.
  3. 03
    Collaborate with data scientists and analysts on data requirements.
  4. 04
    Monitor and maintain data infrastructure for performance and reliability.
  5. 05
    Document and communicate changes and improvements to the team.
  6. 06
    Stay updated with the latest Databricks features and best practices.
Skills & tools

What hiring managers ask for

% of 1 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Databricks
100%
AWS
100%
CI/CD
100%
ETL
100%
Data Governance
100%
Data Quality
100%
Cloud-Native Engineering
100%
Delta Lake
100%
Medallion Architecture
100%
Informatica
100%
Career ladder

From Junior to Principal

A typical UK progression for databricks engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior Databricks Engineer

    0–2 yrs

    Assists in the design and implementation of basic data pipelines. Focuses on learning and contributing to small-scale projects.

  2. Level 2

    Databricks Engineer

    2–5 yrs

    Takes ownership of mid-sized data pipelines. Collaborates with cross-functional teams to ensure data infrastructure meets business needs.

  3. Level 3

    Senior Databricks Engineer

    5–8 yrs

    Leads the design and implementation of complex data pipelines. Mentors junior engineers and drives best practices within the team.

  4. Level 4

    Principal Databricks Engineer

    8+ yrs

    Strategises and oversees the entire data infrastructure. Influences organisational data strategy and leads large-scale projects.

Pathway

How to become a Databricks Engineer

There's no single route, but most people follow some version of these steps.

  1. 1

    Learn the Basics

    Start by mastering the fundamentals of Databricks, including Spark, Delta Lake, and the Databricks Unified Data Analytics Platform.

  2. 2

    Build Small Pipelines

    Gain hands-on experience by designing and implementing small-scale data pipelines. Focus on best practices and efficiency.

  3. 3

    Collaborate with Teams

    Work closely with data scientists, analysts, and other engineers to understand data requirements and improve data infrastructure.

  4. 4

    Lead Mid-Sized Projects

    Take ownership of mid-sized data pipelines. Ensure they are scalable, efficient, and meet business needs.

  5. 5

    Mentor Junior Engineers

    Share your knowledge and experience with junior engineers. Help them grow and develop their skills.

  6. 6

    Influence Data Strategy

    Strategise and influence the organisation's data infrastructure. Lead large-scale projects and drive innovation.

Live jobs

1 live role

Data Platform Engineering Specialist (Databricks)

This role involves designing, developing, and operating cloud-native data platforms with a focus on Databricks on AWS. You will take ownership of the Databricks platform, driving automation, scalability, and security to support data engineering and data science use cases, while ensuring regulatory compliance and operational insight.

Cadent Ansty, Warwickshire, Warwickshire, United Kingdom
On-site Permanent
FAQs

Common questions

  • Essential skills include proficiency in SQL, Python, and Scala, a strong understanding of data warehousing and ETL processes, and experience with Apache Spark and Databricks.

  • Gain experience with data engineering tools and technologies, particularly Databricks and Apache Spark. Consider certifications and hands-on projects to build your portfolio.

  • Responsibilities include designing and implementing data pipelines, optimising data processing workflows, troubleshooting issues, and collaborating with cross-functional teams.

  • The typical career path includes roles such as Junior Databricks Engineer, Databricks Engineer, Senior Databricks Engineer, and Principal Databricks Engineer.

  • Salaries for Databricks Engineers can vary based on experience and location. For specific salary ranges, please refer to the salary section on this page.

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