Job Description

Key Responsibilities

Design and implement scalable, reliable, and secure data architectures. Develop best practices and frameworks for data integration, governance, and security. Define and drive the roadmap for enterprise data solutions aligned with business objectives. Architect, build, and optimize ETL/ELT pipelines using Azure Data Factory (ADF), Databricks, and PySpark. Work with SQL and big data technologies to ensure efficient data processing and storage. Design and manage data lakes, data warehouses, and cloud-based storage solutions. Implement cloud-based data solutions, primarily using Microsoft Azure (Azure Data Factory, Azure Synapse, Azure Databricks). Ensure cost-effective and high-performance cloud solutions for data processing and analytics. Lead and mentor a team of data engineers, ensuring adherence to best practices. Collaborate with stakeholders, including data analysts, business leaders, and software engineers, to define and implement data-driven solutions. Provide technical guidance and architectural direction for complex projects. Ensure high availability, scalability, and performance of data systems. Implement data security policies and ensure compliance with industry standards (GDPR, HIPAA, etc.). Optimize data storage and retrieval for maximum efficiency and cost savings

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Requirements

Proven experience in designing and implementing large-scale data solutions.
Technical Skills

SQL: Advanced skills in query optimization and database management. PySpark: Strong experience in data transformation and processing. Databricks: Hands-on experience in big data frameworks and analytics. Azure Data Factory (ADF): Expertise in orchestrating ETL/ELT pipelines. Cloud Platforms: Strong experience with Azure (preferred), AWS, or GCP. Data Warehousing: Deep understanding of data modeling, data lakes, and data warehouse architectures.
Job Type: Full-time

Pay: ₹470,561.62 - ₹1,816,006.73 per year

Work Location: In person