Description

Key Skills: Azure Data Factory, Snowflake, SQL Server, SSIS, SSRS, ETL, Azure SQL, Event Hub, Data Warehousing, Data Modeling

Good to Have Skills: Experience with GitLab repositories, code promotion processes, and CI/CD implementations. Experience with Harness deployment pipelines and release management practices. Experience with .NET Core and Web API development for data integration and service-based architectures. Knowledge of Azure services such as AKS, Service Bus, Key Vault, App Configuration, and cloud-native application architectures. Experience developing and supporting Windows Services and backend processing components. Experience with Python for data engineering, automation, scripting, and analytics solutions. Experience with real-time event-driven architectures and streaming data solutions. Azure certifications such as Azure Data Engineer Associate (DP-203), Azure Administrator Associate (AZ-104), or Azure Solutions Architect Expert. Experience with FinTech, Banking, Payments, Deposits, Lending, or Financial Services domains. Exposure to AI/ML, Generative AI, and advanced analytics platforms.

Roles & Responsibilities:

• Design, develop, and maintain enterprise data integration solutions using Azure Data Factory, Snowflake, SQL Server, and SSIS.
• Build and support scalable ETL/ELT pipelines for data ingestion, transformation, validation, and data warehousing.
• Develop and optimize Snowflake databases, schemas, stored procedures, tasks, streams, and data-sharing solutions.
• Design and maintain Azure-based data solutions utilizing Azure Data Factory, Event Hub, Azure SQL, and related services.
• Develop and support operational, analytical, and executive reporting solutions using SSRS.
• Create and optimize complex SQL queries, stored procedures, views, and database objects to improve performance and scalability.
• Implement and support CI/CD pipelines using GitLab and Harness for automated deployment of data engineering solutions.
• Collaborate with business stakeholders and technical teams to understand data requirements and deliver scalable solutions.
• Monitor data pipelines, troubleshoot production issues, perform root cause analysis, and implement corrective actions.
• Ensure data quality, data governance, data security, and compliance with enterprise standards.
• Maintain technical documentation, data flow diagrams, deployment procedures, and operational runbooks using Confluence.
• Participate actively in Agile ceremonies including Sprint Planning, Backlog Grooming, Daily Standups, and Retrospectives.
• Work with global teams across multiple time zones to support business-critical applications and reporting platforms.

Experience Required: Minimum 6 to 10 years of experience in Data Engineering, Data Warehousing, and Reporting solutions.

Education: BE/BTech/MCA/MTech/BSc – Computer Science, Information Technology, or related field

Key Skills

Education

Any Graduate