Data Engineer

Unifeye

Greater London

Hybrid

GBP 70,000 - 100,000

Full time

14 days+

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Benefits offered by this job

Databricks focus
Hybrid working
Competitive salary
Bonus
Career development

Job summary

Unifeye is hiring experienced Data Engineers to join our growing delivery team in London and help design, build and deliver modern data platforms on the Databricks Lakehouse Platform. You will work across enterprise engagements, delivering scalable, secure data solutions and collaborating with architects, AI specialists and client stakeholders.

You will contribute to engineering best practices, share knowledge within the team and support Unifeye's growth with hands-on delivery of

Qualifications

  • Experience building production-grade data pipelines with Spark/PySpark.
  • Experience delivering modern data platforms on Databricks.
  • Strong SQL skills and data modeling.

Responsibilities

  • Design and build scalable batch and streaming data pipelines using Spark and Databricks.
  • Develop modern Lakehouse architectures using Delta Lake and Medallion (Bronze, Silver and Gold) design principles.
  • Build robust ingestion frameworks from APIs, files and streaming data sources.
  • Ensure data quality, testing, monitoring and observability across data pipelines.
  • Implement governance, access control and lineage using Unity Catalog.
  • Optimise workloads for performance, scalability and cost efficiency.
  • Collaborate with architects and customers to translate business requirements into production-ready data solutions.
  • Support integration with downstream analytics, BI, machine learning and AI workloads.
  • Contribute to CI/CD pipelines, deployment automation and infrastructure-as-code practices.

Skills

PySpark
SQL
Data modeling
Cloud platforms

Tools

Databricks
Airflow
Terraform

Job description

About Unifeye

Unifeye is a delivery-led, Databricks first consultancy helping organisations unlock the full value of their data and AI.

We're a lean, high growth team based in London, working at the intersection of data, technology and business strategy. We partner with enterprise organisations across industries to solve complex data challenges through modern Lakehouse architectures on Databricks.

Joining Unifeye means more than delivering projects. From day one, you'll be trusted to take ownership, challenge conventional thinking and make a genuine impact. With a high degree of autonomy, you'll help shape client outcomes, influence our technical direction and play a key role in the growth of the business.

The Role

We're looking for experienced Data Engineers to join our growing delivery team and help design, build and deliver modern data platforms on the Databricks Lakehouse Platform.

You'll work across multiple enterprise engagements, helping customers build scalable, secure and governed data solutions while collaborating closely with architects, AI specialists and client stakeholders. You'll play a key role in delivering production-grade data platforms that support analytics, machine learning and AI workloads across industries including financial services, retail and the public sector.

Alongside client delivery, you'll contribute to engineering best practices, share knowledge across the team and support the continued growth of Unifeye.

What You'll Do
  • Design and build scalable batch and streaming data pipelines using Spark and Databricks.
  • Develop modern Lakehouse architectures using Delta Lake and Medallion (Bronze, Silver and Gold) design principles.
  • Build robust ingestion frameworks from APIs, files and streaming data sources.
  • Ensure data quality, testing, monitoring and observability across data pipelines.
  • Implement governance, access control and lineage using Unity Catalog.
  • Optimise workloads for performance, scalability and cost efficiency.
  • Collaborate with architects and customers to translate business requirements into production-ready data solutions.
  • Support integration with downstream analytics, BI, machine learning and AI workloads.
  • Contribute to CI/CD pipelines, deployment automation and infrastructure-as-code practices.
What We're Looking For
Essential
  • Strong commercial experience building production-grade data pipelines using Apache Spark (PySpark preferred).
  • Experience delivering modern data platforms using Databricks or an equivalent Spark-based platform.
  • Strong SQL skills and experience with data modelling.
  • Good understanding of Lakehouse architecture and Delta Lake.
  • Experience working with AWS, Azure or GCP.
  • Experience implementing CI/CD, version control and deployment automation.
  • Strong communication skills and experience working with technical and business stakeholders.
Desirable
  • Experience with Unity Catalog or similar data governance frameworks.
  • Experience with Terraform or Databricks Asset Bundles.
  • Exposure to MLflow, MLOps or AI and Generative AI workloads.
  • Experience with streaming technologies such as Kafka or Structured Streaming.
  • Databricks certification.
  • Previous consulting or client-facing delivery experience.
Why Join Unifeye?

We're building a consultancy where talented people can do their best work.

At Unifeye, you'll have the opportunity to solve meaningful problems, work with leading enterprise organisations and collaborate with some of the UK's most experienced Databricks specialists. As a high-growth business, you'll have the autonomy to make decisions, influence how we work and see the direct impact of your contributions.

We offer:
  • The opportunity to work exclusively with Databricks technologies.
  • High levels of ownership and autonomy from day one.
  • The chance to make a real impact on clients and the growth of the business.
  • Close collaboration with Databricks teams.
  • Continuous learning, certification and career development.
  • Competitive salary, bonus, generous benefits and flexible hybrid working.

If you're passionate about building modern data platforms, enjoy solving complex technical challenges and want to work with some of the UK's leading Databricks specialists, we'd love to hear from you.

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