Job Title: ETL & Data Quality Specialist
Location: Chennai/ Bangalore/ Hyderabad(Primarily looking for Local's. Open for remote candidates as well)
Experience: 10+ years
Budget: Open to discuss
Notice Period: Immediate joiner/ Serving notice with less than 30 days/Notice is less than 20 days
Professional Summary
Seasoned ETL and Data Quality Specialist with 10+ years of experience delivering robust, scalable data integration and data quality frameworks across enterprise environments. Strong hands-on expertise with Informatica IDMC (CDI, CDQ), ETL pipelines, data profiling, cleansing, and validation. Adept at implementing high-quality data solutions aligned with governance, compliance, and downstream analytical requirements. MDM experience included as a secondary skillset, supporting match/merge logic, survivorship, and metadata structures.
Core Competencies
- ETL Architecture & Data Pipelines
- IDMC CDI & CDQ (Primary)
- Enterprise Data Quality Frameworks (Primary)
- Data Profiling, Cleansing, Standardization
- API Integrations & Cloud Data Ingestion
- MDM (OnPrem & SaaS) Secondary
- Match/Merge & Survivorship (Secondary)
- Data Modeling & Governance Support
Primary Skills
- Strong hands-on expertise in Informatica IDMC CDI and CDQ.
- Proven experience in building large-scale ETL pipelines and DQ frameworks.
- Solid understanding of data modeling, metadata management, and integration architecture.
- Exposure to Informatica MDM SaaS/OnPrem, including match/merge and survivorship.
- Proficiency with API integrations, cloud platforms, and automation.
- Strong analytical, communication, and problemsolving abilities.
- Ability to work independently and drive technical outcomes in fast-paced environments.
Secondary Skills
- Familiarity with multi-domain MDM environments.
- Exposure to data governance and stewardship processes.
- Knowledge of AWS/Azure cloud ecosystems.
Key Responsibilities
- Lead design and development of enterprise ETL pipelines using Informatica CDI and related integration services.
- Own end-to-end Data Quality implementation, including profiling, cleansing, enrichment, and rule-based validation.
- Collaborate with business and IT stakeholders to define data quality KPIs, governance standards, and integration patterns.
- Integrate upstream and downstream systems using IICS, APIs, and cloud-native services.
- Support MDM teams with configuration of match/merge, survivorship, and metadata structures (secondary responsibility).
- Conduct root-cause analysis for data issues and implement remediation workflows.
- Mentor junior engineers and contribute to reusable frameworks and accelerators.
