Data Engineer @ Ework Group

2 weeks ago

Remote Wrocław, Czech Republic Ework Group Full time

Azure Databricks (PySpark, Spark SQL; Unity Catalog; Jobs/Workflows). Azure data services: Azure Data Factory, Azure Key Vault, storage (ADLS), fundamentals of networking/identities. Python for data engineering (APIs, utilities, tests). Azure DevOps (Repos, Pipelines, YAML) and Git-based workflows. Experience operating production pipelines (monitoring, alerting, incident handling, cost control). 💻 Ework Group - founded in 2000, listed on Nasdaq Stockholm, with around 13,000 independent professionals on assignment - we are the total talent solutions provider who partners with clients, in both the private and public sector, and professionals to create sustainable talent supply chains. With a focus on IT/OT, R&D, Engineering and Business Development, we deliver sustainable value through a holistic and independent approach to total talent management. By providing comprehensive talent solutions, combined with vast industry experience and excellence in execution, we form successful collaborations. We bridge clients and partners & professionals throughout the talent supply chain, for the benefit of individuals, organizations and society. 🔹 For our Client we are looking for Senior Data Engineer 🔹 Preferred candidates are based in Wrocław, but applicants from other locations in Poland will also be considered. ✔️ Main assignment: Maintain and evolve the data flows used by the Picto application: Azure + Databricks pipelines (ADF + notebooks) that ingest data from APIs using Ingestion Framework, transform it (PySpark/Spark SQL), and deliver trusted datasets. ✔️ Tech stack you’ll meet: Azure, Databricks (PySpark/Spark SQL, Unity Catalog, Workflows), ADF, ADLS/Delta, Key Vault, Azure DevOps (Repos/Pipelines YAML), Python, SQL ,[Own day-to-day operations of Picto data pipelines (ingest → transform → publish), ensuring reliability, performance and cost efficiency., Develop and maintain Databricks notebooks (PySpark/Spark SQL) and ADF pipelines/Triggers; manage Jobs/Workflows and CI/CD., Implement data quality checks, monitoring & alerting (SLA/SLO), troubleshoot incidents, and perform root-cause analysis., Secure pipelines (Key Vault, identities, secrets) and follow platform standards (Unity Catalog, environments, branching)., Collaborate with BI Analysts and Architects to align data models and outputs with business needs., Document datasets, flows and runbooks; contribute to continuous improvement of the Ingestion Framework.] Requirements: Azure, Databricks, PySpark, Azure Data Factory, Azure DevOps, AI

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