Data Analysts ETL SQL Informatica

Technology->Analytics - Solutions->SQL Server - Analytics->SQL,Technology->Informatica ETL Developer->ETL Developer

Key Responsibilities:

• Gather and analyze business requirements to define data needs, metrics, and reporting outcomes.
• Perform data profiling, validation, and reconciliation to ensure accuracy, completeness, and consistency.
• Develop, maintain, and optimize ETL workflows using Informatica to load and transform data across systems.
• Write and tune SQL queries for data extraction, transformation, and analytical use cases.
• Create and maintain documentation for ETL mappings, data flows, source-to-target mappings, and business logic.
• Monitor ETL jobs, troubleshoot failures, and implement fixes to improve stability and performance.
• Collaborate with cross-functional teams to deliver datasets and insights aligned to timelines and quality standards.
• Support UAT and production releases by validating outputs and ensuring smooth deployments in a hybrid work setup. Minimum Qualifications:
• Bachelor’s or Master’s degree in BTech, BCA, BSc, MCA, MSc, or MTech (or equivalent).
• 3–5 years of experience in data analysis with strong hands-on SQL skills.
• 3–5 years of experience working with ETL concepts and building data pipelines.
• Practical experience using Informatica for ETL development and maintenance.
• Strong understanding of data quality checks, data validation, and troubleshooting data issues. Preferred Qualifications:
• Experience optimizing SQL queries and ETL performance for large datasets and recurring batch processes.
• Strong knowledge of data warehousing concepts, dimensional modeling, and source-to-target mapping practices.
• Experience creating clear analytical outputs such as dashboards/reports or curated datasets for stakeholders.
• Familiarity with release processes, UAT support, and production monitoring in enterprise environments.
• Ability to communicate findings and data logic clearly to both technical and non-technical audiences while working effectively in a hybrid model. Good to have skills: Data Warehousing, Dimensional Modeling, Data Profiling, Performance Tuning, Data Quality Management