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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Azure Databricks Data Engineer - Banking Client - **Company:** Salt - **Location:** Brussel, Belgium - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Clean Code Principles, Artificial Intelligence, Business Analytics Applications, Automation of Tests, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Code Review, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, DevOps, Python (Programming Language), Key Management, Metadata, Meta-Data Management, Operational Databases, Performance Tuning, Query Optimization, Standard Sql, Azure Data Lake, Scala (Programming Language), Secure Coding, Software Engineering, SQL Databases, Data Streaming, YAML, Data Logging, Data Processing, Azure Data Factory, Apache Spark, Caching, Git, Data Lakes, Pyspark, Deployment Automation, Apache Kafka, Data Management, Machine Learning Operations, Software Coding, Terraform, Azure Synapse Analytics, Software Version Control, Data Pipelines, Databricks - **Published:** August 28, 2026 - **Apply:** https://www.adzuna.be/details/5859285921 ## About the Role You should have at least 5 years of hands-on Data Engineering / Data Application Development experience, ideally within large enterprise environments. Core Technical Skills Strong hands-on experience with: * Azure Databricks * Python * PySpark * Apache Spark * Scala * SQL * ETL / ELT pipeline development * Delta Lake / Lakehouse architecture * Azure Data Factory * Azure Data Lake Storage * Azure DevOps / CI/CD We are particularly interested in candidates who can demonstrate that they have personally designed and developed production Databricks/PySpark solutions, rather than only managing teams or defining architecture. Highly Desirable Experience with any of the following would be advantageous: * Spark performance optimisation * Databricks Auto Loader * Delta Live Tables * Unity Catalog * Medallion / Bronze-Silver-Gold architecture * Streaming data pipelines * Azure Event Hubs * Kafka * Azure Synapse * Azure Key Vault * Azure DevOps YAML * Terraform * Data quality frameworks * Metadata management and lineage * MLflow / MLOps * AI/ML data pipelines * Reusable data-engineering frameworks or libraries * Enterprise security and governance Certifications Relevant certifications are advantageous, particularly: * Microsoft Azure Data Engineer * Microsoft Azure Developer * Microsoft Azure Solutions Architect * Microsoft Azure DevOps Engineer * Databricks Certified Data Engineer Associate * Databricks Certified Data Engineer Professional * Databricks Certified Developer for Apache Spark The Profile That Will Stand Out The strongest candidate will be someone who can say: "I personally build production Azure Databricks solutions. I write Python/PySpark code, build and optimise Spark pipelines, work with Delta Lake and ADF, automate deployments through CI/CD, troubleshoot production issues and understand how to engineer scalable data solutions rather than simply design them." This is not primarily a BI, reporting or high-level Data Architecture position. We are looking for a genuinely hands-on senior engineer who is comfortable getting into the code. ## Description We are looking for an experienced Senior Azure Databricks Data Engineer to join a large-scale enterprise data transformation programme within a complex financial services environment. This is a hands-on engineering position for someone who enjoys designing, developing and optimising production-grade data solutions rather than operating purely at architecture or management level. You will work within a modern Microsoft Azure and Databricks ecosystem, building scalable data pipelines, Lakehouse solutions and reusable engineering components that support analytics, applications and emerging AI/ML use cases. The role combines Data Engineering, Databricks/Spark development and software engineering, so we are particularly interested in engineers with strong coding skills and experience taking data solutions from design through to production. What You'll Be Doing: Azure Databricks & Data Engineering * Design, build, test and maintain scalable data engineering solutions using Microsoft Azure and Azure Databricks. * Develop production-grade ETL/ELT pipelines using Python, PySpark, Scala and SQL. * Build data-processing applications covering ingestion, transformation, enrichment, validation and serving. * Develop Delta Lake / Lakehouse solutions using modern data engineering patterns. * Design and implement Bronze, Silver and Gold / Medallion architectures where appropriate. * Build reliable batch and streaming data-processing workflows. * Develop curated datasets and transformation layers supporting analytics, reporting, applications and AI/ML use cases. Databricks & Apache Spark * Develop and maintain Databricks notebooks, jobs and workflows. * Build and optimise Apache Spark / PySpark workloads operating across large datasets. * Improve Spark performance through appropriate partitioning, caching, cluster configuration and query optimisation. * Implement schema evolution, incremental processing and robust data-quality controls. * Develop reusable Spark/Python components, libraries and engineering frameworks. * Apply appropriate Delta Lake optimisation and data-management techniques. * Troubleshoot and optimise production data pipelines for performance, scalability, reliability and cost. Azure Data Platform Work across a modern Azure data ecosystem including: * Azure Databricks * Apache Spark / PySpark * Delta Lake * Azure Data Lake Storage (ADLS) * Azure Data Factory * Azure Synapse * Azure Event Hubs / streaming patterns * Azure Key Vault * Azure DevOps * Azure monitoring and logging capabilities You will work closely with Cloud, Architecture and Platform teams to ensure solutions are secure, scalable, observable and aligned with enterprise standards. Software Engineering & Application Development This role goes beyond traditional ETL development. You will apply strong software engineering practices to data applications, including: * Modular and reusable development * Clean, maintainable code * Automated testing and validation * Error handling and logging * Code reviews * Git/version control * Technical documentation * Reusable libraries and frameworks You will be expected to contribute to the overall quality of the engineering environment rather than simply delivering individual pipelines. DevOps & CI/CD * Build and maintain CI/CD processes for data applications. * Deploy Databricks and data-engineering code across development, test and production environments. * Work with Azure DevOps and YAML pipelines. * Collaborate with DevOps and Cloud teams on environment configuration and deployment. * Apply release-management and environment-promotion best practices. * Work with Terraform / Infrastructure as Code where required. Terraform expertise is beneficial, but this is primarily a Data Engineering and application-development role rather than an Infrastructure Engineering position. Data Quality, Security & Governance * Build data-quality controls and validation into engineering pipelines. * Implement appropriate logging, monitoring and operational alerting. * Work with enterprise security and access-management standards. * Apply secure coding and cloud data-engineering practices. * Support metadata, lineage and governance requirements. * Consider performance and cloud cost when designing and developing solutions. Technical Leadership As a senior member of the engineering team, you will also: * Work closely with Data, Architecture, AI, Cloud, DevOps and application teams. * Translate complex business and analytical requirements into practical engineering solutions. * Contribute to technical design and engineering standards. * Conduct code reviews and provide technical guidance. * Support and mentor less experienced engineers. * Help establish reusable development patterns and engineering best practices. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [CI/CD with Github Actions](https://www.wearedevelopers.com/videos/856-ci-cd-with-github-actions) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Jobs in Tech: The State of the European Market](https://www.wearedevelopers.com/magazine/575-jobs-in-tech-the-state-of-the-european-market) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)