Data Engineer

Tech Stack & Key Competencies

Cloud & Infrastructure

• Hands-on experience with Microsoft Azure (Data & Analytics ecosystem)
• Proficiency in Azure DevOps, Terraform (Infrastructure as Code, CI/CD pipelines)
• Solid understanding of cloud security, networking, and monitoring

Data Engineering & Pipelines

• Strong expertise in Apache Spark (including performance tuning & optimization)
• Deep experience with Databricks on Azure
• Proficient in Delta Lake, Azure Data Factory (complex pipelines)
• Experience working with Azure Data Lake Storage Gen2 (ADLS Gen2)
• Familiarity with Azure Synapse Analytics (serverless preferred)

Programming & Querying

• Advanced hands-on skills in Python
• Strong experience writing and optimizing complex SQL queries

Big Data & Architecture

• Experience designing enterprise-grade Big Data architectures on Azure
• Ability to evaluate architectural components (Databricks vs. Snowflake vs. Microsoft Fabric, etc.)
• Proven track record working on PoCs, MVPs, and solution prototyping

Streaming & Real-Time Processing

• Hands-on experience with Kafka, Spark Structured Streaming, or cloud-native streaming alternatives

Other Tools & Concepts

• Familiarity with Microsoft Fabric (a plus)
• Strong understanding of DevOps and CI/CD best practices
• Experience working directly with customers (e.g., technical consulting, stakeholder engagement)