Data Engineer

3+ years of experience in data engineering, data integration, business intelligence engineering, or a related technical role. 3+ years of experience writing, optimising, and troubleshooting SQL, including T-SQL, stored procedures, views, indexing strategies, and query performance tuning. Hands-on experience designing, building, and supporting ETL/ELT pipelines using Azure Data Factory and/or Microsoft Fabric Pipelines. Hands-on experience developing data processing and transformation logic using Azure Databricks notebooks, Microsoft Fabric notebooks, PySpark, Spark SQL, Python, or similar technologies. Strong Microsoft SQL Server and relational database design principles skills. Experience with Azure data platform services such as Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, and related cloud data services. Strong knowledge and in depth work with Microsoft Fabric components such as Pipelines, Notebooks, Lakehouses, Warehouses, Dataflows, and semantic models. Experience building reliable data ingestion and transformation processes from APIs, flat files, databases, web services, cloud storage, and other external data sources Hands on experience implementing data validation, reconciliation, monitoring, logging, and alerting processes for production data pipelines. Experience supporting production data workloads, including troubleshooting failures, optimizing performance, and improving pipeline reliability. Prior experience modernizing or migrating legacy ETL processes from SSIS, SQL Server, or on-premises environments to Azure or Microsoft Fabric is strongly preferred. Ability to work independently on moderately complex data engineering tasks while collaborating effectively in a team-oriented environment. Bachelor’s degree in Computer Science, Information Technology, Data Analytics, a related field, or equivalent professional experience. Power BI, semantic models, or other data visualization and analytics tools experience is a plus. Experience with Customer Data Platforms, CDPs, database marketing, marketing analytics, or client data onboarding environments is a plus. Working knowledge with AWS or Google Cloud Platform is a plus. Strong analytical, problem-solving, and critical thinking skills. Excellent verbal and written communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.