Job Summary
Description:
In the VCE PML team, we make the right Data Available for Analytics Value and drive the growth of Analytics Capabilities.
In PML Team, you will support the complete lifecycle of enterprise data: Source Systems → Data Integration → Unified Data Platform → Data Marts, Universes & Semantic Models → BI & Analytics → AI & Data Products.
You will:
design and maintain data integration pipelines that connect enterprise source systems to the Unified Data Platform (Data Lake)
create and maintain structured analytical datasets, including data marts, universes and semantic models, that enable business users to easily access trusted and well-defined data
be a partner with business teams to deliver high-value reporting and analytics solutions, including: Interactive dashboards in Microsoft Power BI, Enterprise reports using SAP BusinessObjects, Domain data products and analytical datasets, Operational and strategic reporting solutions
supports the development and deployment of advanced analytics and AI solutions that leverage enterprise data. These include: Predictive analytics models, Machine learning solutions, AI-powered decision support tools, Intelligent data products
Key responsibilities
• Collaborate with business stakeholders to understand requirements and translate them into data engineering solutions.
• Design, build, and maintain end-to-end data pipelines for ingestion, transformation, and processing using Azure services, Databricks, IICS, and Azure Synapse.
• Develop advanced transformation logic in Databricks and IICS to support complex business use cases.
• Knowledge of modern Data Modeling and Design concepts
• Set up and manage DevOps environments, including configurations, CI/CD pipelines, releases, deployments, and hotfix management.
• Write clean, efficient, and maintainable code in SQL, Python, PySpark, and scripting languages.
• Actively contribute in an Agile environment, ensuring transparency, collaboration, and continuous improvement.
Required skills
• Several years of experience in Data Engineering.
• Strong hands-on experience with Databricks, Azure Services (Azure Data Factory, Azure SQL Database, Azure Key Vault), IICS, and Azure Synapse.
• Advanced programming skills in Python, PySpark, and SQL.
• Experience designing and implementing CI/CD pipelines and managing Azure DevOps environments.
• Knowledge of API integrations and enterprise data architecture, theoretical AI knowledge
• Experience working in Agile/Scrum teams.
• Strong analytical and problem-solving skills
Key Responsibilities
2. To develop and guide the team members in enhancing their technical capabilities and increasing productivity
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To prepare and submit status reports for minimizing exposure and risks on the project or closure of escalations.