Job description
Come join us In the Data Engineer role, you’ll expand your expertise by contributing to modern initiatives across a variety of industries and business domains. You’ll work with a broad toolset, with responsibilities including: What you’ll do Creating, developing, and operating scalable, efficient, and dependable data pipelines Delivering end-to-end data platforms, including data architecture and ETL implementations Partnering with data scientists, analysts, and engineering teams to integrate data and improve end-to-end performance Applying best practices for data governance, quality, and security across the data estate Tuning and streamlining data workflows to maximize reliability and throughput Keeping current with new trends and advancements in data engineering Supporting and coaching junior data engineers through mentoring and knowledge sharing Opportunity to grow your skills in advanced AI technologies Tech stack You’ll use a range of tools depending on the project, however our core stack typically includes: Databricks, Py.
Spark, Azure cloud and services (Data Lake, SQL Database, Azure Databricks, Azure Data Factory), SQL, Python, MS Fabric . Skills and experiences : Must-have skills To be successful in this position, you should have hands-on commercial experience with: Azure cloud and services (e.g. Azure Data Factory, Data Lake, SQL Database, Azure Databricks) Databricks (commercial project experience) Python and Py.
Spark for building and operating data solutions SQL for querying, transforming, and validating data Core data engineering practices (ETL, data modeling, data warehousing, data governance) English at B2 level (or higher) Nice to have: Hands-on experience with MS Fabric Familiarity with containerization and orchestration (Docker/Kubernetes) Understanding of machine learning concepts and frameworks (e.
g. MLflow, Tensor. Flow) Knowledge or experience with LLMs and orchestration frameworks .