Role Overview:

We are seeking street-smart and technically strong Senior Data Engineers / Leads who can take ownership of designing and developing cutting-edge data and AI platforms using Azure-native technologies and Databricks. You will play a critical role in building scalable data pipelines, up-to-date data architectures, and intelligent analytics solutions.

Key Responsibilities:

- Design and implement scalable, metadata-driven frameworks for data ingestion, quality, and transformation across both batch and streaming datasets.
- Develop and optimize end-to-end data pipelines to process structured and unstructured data, enabling the creation of analytical data products.
- Build robust exception handling, logging, and monitoring mechanisms for better observability and operational support.
- Take ownership of complex modules and lead the development of critical data workflows and components.
- Provide guidance to data engineers and peers on best practices.
- Collaborate with cross-functional teams—including business consultants, data architects & scientists, and application developers—to deliver impactful analytics solutions.

Required Qualifications:

- 5+ years of overall technical experience,



with a minimum of 2 years of hands-on experience with Microsoft Azure and Databricks.
- Proven experience delivering at least one end-to-end Data Lakehouse solution on Azure Databricks using the Medallion Architecture.
- Strong working knowledge of the Databricks ecosystem, including: PySpark, Notebooks, Structured Streaming, Unity Catalog, Delta Live Tables, Workflows, and SQL Warehouse.
- Advanced programming, unit testing, and debugging skills in Python and SQL.
- Hands-on experience with Azure-native services such as: Azure Data Factory, ADLS Gen2, Azure SQL Database, and Event Hub.
- Solid understanding of data modeling techniques, including both Dimensional and Third Normal Form (3NF) models.
- Exposure to developing LLM/Generative AI-powered applications.
- Must have excellent understanding of CI/CD workflows using Azure DevOps.
- Bonus: Knowledge of Azure infrastructure, including provisioning, networking, security, and governance.

Educational Background:

- Bachelor's degree (B.E/B.Tech) in Computer Science, Information Technology, or a related field from a reputed institute (preferred).

Skills: Spark, Azure Databricks, Pyspark, Azure Data Factory, Azure Data Lake, Sql, Python

Experience: 6.00-11.00 Years

📌 Azure Data Engineer (Hyderabad)
🏢 Tiger Analytics
📍 Hyderabad