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