About ProcDNA
ProcDNA is a global consulting firm. We fuse design thinking with cutting-edge technology to create game-changing Commercial Analytics and Technology solutions for our clients. We're a passionate team of 400+ across 6 offices, all growing and learning together since our launch during the pandemic. Here, you won't be stuck in a cubicle - you'll be out in the open water, shaping the future with brilliant minds. At ProcDNA, innovation isn't just encouraged; it's ingrained in our DNA. Ready to join our epic growth journey
What We Are Looking For
We are looking for an experienced Cloud Data Engineer with 5–7 years of expertise in designing and delivering scalable, high-performance data platforms on Microsoft Azure. Strong hands-on experience in building data pipelines, data modeling, and data warehousing is essential. The role requires understanding of distributed data processing using Azure Databricks/Spark, along with exposure to batch and real-time architectures. Proven experience in designing Azure data solutions, implementing data quality frameworks, and ensuring governance using Azure-native services is expected. Hands-on experience with DevOps/DataOps practices, CI/CD pipelines, and deployments on Azure is required. Strong problem-solving skills, ownership mindset, and ability to collaborate with stakeholders are key.
What You'll Do
- Design and architect scalable data platforms and pipelines using Azure services such as Azure Data Factory, Azure Databricks, and ADLS.
- Build and optimize complex ETL/ELT pipelines for batch and real-time data processing using Databricks/Spark.
- Develop data models, data warehouse solutions, and optimized storage structures using Azure services.
- Implement data quality checks, validation frameworks, and monitoring to ensure reliable and accurate data.
- Optimize data pipelines and infrastructure for performance, scalability, and cost efficiency.
- Collaborate with business, analytics, and product teams to deliver data solutions aligned with business needs.
What You'll Need
- 5–7 years of hands-on experience in data engineering with strong expertise across the Microsoft Azure ecosystem.
- Proven experience working with Azure Data Factory, Azure Databricks, ADLS, and Apache Spark for building scalable and efficient data pipelines.
- Strong programming skills in Python and advanced SQL, with the ability to write optimized, reusable, and production-grade code.
- Solid understanding of data warehousing concepts, data modeling techniques, and modern big data architectures.
- Hands-on experience with DevOps/DataOps practices, including CI/CD pipelines, Git-based version control, and deployment of data solutions in production environments.
- Good understanding of data quality frameworks, validation techniques, monitoring, and troubleshooting to ensure reliable and accurate data systems.
Skills: azure data factory,spark,azure databricks,sql,adls,etl,azure,python
