YOUR KEY RESPONSIBILITIES:

• Design, build, and maintain scalable ELT/ETL pipelines using Azure Data Factory, ensuring reliability and performance at terabyte scale.

• Own end-to-end pipeline health: monitoring, alerting, incident response, and continuous improvement.

• Identify and resolve bottlenecks across ingestion, transformation, and serving layers; drive measurable performance gains.

• Contribute to the design and evolution of our medallion architecture and golden layer strategy.

• Implement data ingestion processes from multiple heterogeneous sources, ensuring accuracy, completeness, and consistency.

• Support the migration from SAP BW, ensuring data continuity and quality throughout.

• Ensure data integrity and availability through appropriate storage solutions, partitioning strategies, and access controls.

• Work autonomously to deliver complex data engineering tasks with minimal supervision, while proactively communicating progress and blockers.

• Collaborate closely with data scientists, BI analysts, and business stakeholders to understand requirements and translate them into technical solutions.

• Participate in agile ceremonies, contribute to sprint planning, and own your backlog items end-to-end.

ARE THESE YOUR SECRET INGREDIENTS

• Bachelor's degree in Information Technology, Computer Science, or related field.

• 5+ years of experience in data engineering with a strong focus on Azure (Azure Data Factory, Azure Data Lake Storage, Fabric).

• Proven experience designing and building production-grade data pipelines that handle large volumes of data reliably.

• Strong SQL skills and experience with data modelling, schema design, and query optimization.

• Hands-on experience with Databricks (PySpark / Spark SQL) for large-scale data transformation.

• Proficiency in at least one programming language: Python (preferred), Scala, or C#/.NET.

• Solid understanding of data warehouse and lakehouse concepts.

• Strong ability to work independently, manage your own priorities, and deliver under ambiguity.

• Excellent communication skills - able to translate technical concepts for business stakeholders and vice versa.

• Excellent problem-solving and debugging skills.

• Excellent spoken and written English

• Communication, organizational and analytical skills

Preferred Qualifications:

• Experience with real-time or near-real-time streaming pipelines (Azure Event Hubs, Apache Kafka, Spark Streaming).

• Hands-on experience with CI/CD for data pipelines using Azure DevOps, Git, and infrastructure-as-code (Terraform).

• Familiarity with DevSecOps principles and experience working within the SAFe Agile framework.

• Knowledge of SAP BW (extractors, transformations, queries, data export) and experience supporting BW migrations.

• Experience with big data technologies such as Hadoop, Spark, and Hive, and large data volume management.

• Strong analytical and problem-solving mindset - you enjoy finding root causes, not just symptoms.

• Experience with Power BI and DAX for building analytical models and connecting to enterprise data.

Senior Azure Data Engineer