DNAHL_SQL, Databricks, PySpark, Delta lake, Azure Data Factory, Logic Apps, and Airflow

• 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