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Data Engineer

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Onsite

Data Engineer

Tiger Analytics

Data Engineer

Skills

SQL QueriesPythonDatabricksData AnalysisAIPySparkAzure

11 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

11 October 2026

What they need


We are seeking street-smart and technically strong Data Engineers 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, modern 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.

EXPERTISE
3+ 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.

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