Data Engineer Development Lead

Position Overview

We are seeking a Senior Data Engineer to drive cloud data modernization and build scalable, AI-ready data platforms. This role emphasizes expertise in Databricks, PySpark, Azure Data Factory, Logic Apps, and Airflow, with a strong focus on orchestration, pipeline reliability, and end-to-end data workflow management.

Key Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks (PySpark), ADF, Logic Apps, and Airflow
• Develop and manage end-to-end orchestration frameworks integrating Airflow DAGs with ADF and Logic Apps
• Implement advanced workflow orchestration patterns (event-driven, micro-batch, hybrid scheduling)
• Ensure pipeline dependency management, execution reliability, and operational excellence
• Build high-performance ETL/ELT pipelines using Databricks and Delta Lake architecture
• Implement data observability, monitoring, and alerting mechanisms across workflows
• Optimize pipelines and workflows for performance, scalability, and cost efficiency
• Integrate pipelines with Azure services such as ADLS Gen2, Blob Storage, and event triggers
• Implement CI/CD for pipelines and workflows using GitHub Actions or equivalent
• Ensure data quality, governance, and security compliance
• Collaborate with data science teams for ML/GenAI data readiness
• Mentor junior engineers and drive best practices for orchestration and pipeline design

Required Qualifications

• 10+ years of experience in data engineering
• Highly proficient in Databricks (PySpark, Delta Lake), Azure Data Factory (ADF), Azure Logic Apps, and Apache Airflow
• Strong programming skills in Python and advanced SQL
• Experience in building orchestrated data platforms with multi-tool integration
• Strong understanding of ETL/ELT patterns and orchestration frameworks
• Experience in cloud-native data architectures (Azure preferred)
• Hands-on experience with monitoring, logging, and pipeline reliability

Data Engineer (Databricks +Pyspark) JD + ADF/Logic Apps (Highly Proficient) + Airflow

Preferred Qualifications

• Experience with event-driven architecture and API integrations
• Exposure to AI/ML data pipelines and MLflow
• Knowledge of Data Lakehouse architectures and governance frameworks
• Azure / Databricks certifications, Must Have Skills:Design, build, and maintain scalable data pipelines using Databricks (PySpark), ADF, Logic Apps, and Airflow

Build high-performance ETL/ELT pipelines using Databricks and Delta Lake architecture, Strong knowledge on Databricks, Orchestration workflow using ADF, Logic Apps, Airflow., Nice to have skills - .Net , C#