On Time Solutions - Lead / Azure Data Engineer - ETL / Metadata

Designation : Lead Azure Data Engineer

Experience : 5+

Location : Bangalore / Hyderabad

Skills : Azure Data Engiineer, ADF, ADB, ADLS, Python, Pypark

Key technical skills :

• Hands-on experience in designing and building scalable data pipelines using Databricks with PySpark, supporting batch and near-real-time ingestion, transformation, and processing.
• Ability to optimize Spark jobs and manage large-scale data processing using RDD / DataFrameAPIs.
• Demonstrated expertise in partitioning strategies, file format optimization (Parquet / Delta), and Spark SQL tuning.
• Skilled in governing and manage data access for Azure Data lakehouse with Unity Catalog. Experience in configuring data permissions, object lineage, and access policies with Unity Catalog.
• Understanding of integrating Unity Catalog with Azure AD, external metastores, and audit trails.
• Experience in building efficient orchestration solutions using Azure data factory, Databricks Workflows.
• Ability to design modular, reusable workflows using tasks, triggers, and dependencies.
• Skilled in using dynamic expressions, parameterized pipelines, custom activities, and triggers.
• Familiarity with integration runtime configurations, pipeline performance tuning, and error handling strategies.
• Good experience in implementing secure, hierarchical namespace-based data lake storage for structured / semi-structured data, aligned to bronze-silver-gold layers with ADLS Gen2.
• Hands-on experience with lifecycle policies, access control (RBAC / ACLs), and folder-level security.
• Understanding of best practices in file partitioning, retention management, and storage performance optimization.
• Capable of developing T-SQL queries, stored procedures, and managing metadata layers on Azure SQL
• Comprehensive experience working across the Azure Cloud ecosystem, including networking, security, monitoring, and cost management relevant to data engineering workloads.
• Experience in writing modular, testable Python code used in data transformations, utility functions, and packaging reusable components.
• Familiarity with Python environments, dependency management (pip / Poetry / Conda), and packaging libraries.
• Ability to write unit tests using PyTest / unittest and integrate with CI / CD pipelines.
• Able to prepare Design documents for developmentadopting code analyzers and unit testing frameworks.
• Write clear and concise documentation leveraging industry standard practices & guidelines.

(ref : hirist.tech)