Job Description

As

Promade Solutions

continues to grow and deliver cutting-edge data and analytics solutions to both existing and new customers, we are looking for

experienced Databricks Data Engineers

who are passionate about building scalable, reliable, and high-performance data platforms.

As a Databricks Data Engineer, you will play a key role in designing, developing, and optimising modern data pipelines and lakehouse architectures. You will work closely with analytics, product, and engineering teams to deliver trusted, production-ready datasets that power reporting, advanced analytics, and data-driven decision-making.

We are looking for engineers with an inquisitive mindset, a strong understanding of data engineering best practices, and a passion for continuous learning. You should be comfortable taking ownership, influencing technical decisions, and contributing ideas as part of a collaborative and growing engineering team.

We value

close collaboration over excessive documentation

, so strong communication and interpersonal skills are essential. To succeed in this agile and forward-thinking environment, you should have solid experience with Databricks, cloud platforms, and modern data engineering tools and architectures.

Key Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines for batch and streaming data workloads Develop and optimise Databricks Lakehouse solutions using Apache Spark and Delta Lake Design and maintain data models, data warehouses, and lake/lakehouse architectures Implement data quality, validation, observability, and monitoring frameworks Optimise data pipelines for performance, reliability, and cost efficiency Collaborate with cross-functional teams to deliver trusted, production-grade datasets Work extensively with Azure cloud services, including Azure Databricks, Azure Data Factory, Azure SQL DB, Azure Synapse, and Azure Storage Develop and manage stream-processing systems using tools such as Kafka and Azure Stream Analytics Write clean, maintainable Python and SQL code and develop high-quality Databricks notebooks Support CI/CD pipelines, source control, and automated deployments for data workloads Contribute to improving data engineering standards, frameworks, and best practices across the organisation

Essential Skills & Experience

7+ years of experience in

Data Engineering

roles Strong hands-on experience with

Databricks

and Apache Spark

Mandatory: Databricks Certified Professional credential

Excellent proficiency in SQL and Python Strong understanding of distributed data processing, data modelling, and modern data architectures Experience working with

cloud data platforms

such as Azure Synapse, Snowflake, Redshift, or BigQuery Hands-on experience with

batch and streaming

data pipelines Experience with orchestration and transformation tools such as

Airflow,

dbt

, or similar Solid understanding of

CI/CD, Git, and DevOps

practices for data platforms Ability to work autonomously, take ownership, and deliver high-quality solutions Strong communication skills with the ability to explain technical concepts clearly to both technical and non-technical stakeholders

Desirable Skills

Experience with real-time data streaming and event-driven architectures Exposure to data governance, security, and access control in cloud environments Experience across multiple cloud platforms (AWS, Azure, GCP) Familiarity with DataOps, MLOps, or analytics engineering practices
Job Type: Full-time

Pay: 50,000.00-60,000.00 per year

Benefits:

Company pension On-site parking Work from home
Work Location: Hybrid remote in Altrincham WA14 1TD