Immediate Joiner

Location:-PAN India

Experience:-7-14 Years

Hybrid mode

Key Responsibilities

- Review approved CDE registers, DQ rule catalogs, business definitions, thresholds, pain points, and source-to-field mappings for each rollout wave.
- Profile SAP-originated and other prioritized datasets landed in Azure Data Lake Storage, and analyze completeness, validity, uniqueness, consistency, accuracy, and integrity issues.
- Design and configure reusable Informatica Cloud Data Quality assets, including rule specifications, mappings, dictionaries/reference data, scorecards, validation controls, and monitoring jobs.
- Implement technical DQ rules mapped to CDEs and business rules; configure thresholds, pass/fail logic, alerts, exception capture, and rerun processes.
- Establish exception handling and support remediation workflows for failed records, including traceability to source data and responsible data owners or stewards.
- Support integration of DQ rules and results with IDMC catalog, workflows, metadata, lineage, monitoring dashboards, data marketplace, and enterprise data portal capabilities.
- Validate source connectivity, profiling, metadata harvesting, and data movement between the enterprise data lake or landing area, IDMC, and the DQ repository.
- Work with SAP SMEs to validate SAP tables, fields, extraction logic, cross-table relationships, landed file structures, and interpretation of rule failures.
- Create functional and non-functional test plans, test cases, test data, execution evidence, defect logs, and traceability matrices.
- Perform unit, system, integration, regression, UAT, and production validation; diagnose defects and tune rules, jobs, and thresholds based on stakeholder feedback.
- Support deployment across development, QA, UAT, and production environments, including release packaging, configuration migration,



change records, go-live checks, and rollback readiness.
- Monitor job runs and DQ scores, troubleshoot failures, optimize performance, and provide hypercare and production stabilization support.
- Maintain technical design details, configuration inventories, rule documentation, deployment records, operating procedures, runbooks, and knowledge-transfer materials.
- Participate in sprint planning, estimation, daily delivery ceremonies, demos, status reporting, risk/dependency management, and sign-off preparation.

Primary Deliverables
- Configured profiling tasks and documented profiling results for prioritized tables.
- Production-ready DQ rule libraries for rollout waves
- Implemented validation, alerts, scorecards, exception handling, and rerun processes.
- Validated IDMC connectivity and integration with the enterprise data lake and DQ repository.
- DQ outputs integrated with catalog, lineage, workflows, dashboards, marketplace, and portal capabilities as applicable.
- Deployment packages and evidence supporting QA, enterprise architecture, security, compliance, CAB, and production approvals.
- Technical configuration documentation, operating procedures, runbooks, and knowledge-transfer materials.
- Hypercare support, issue resolution, and stabilization outputs following each release.

Required Technical Skills
- Strong hands-on experience with Informatica IDMC, especially Cloud Data Quality and Cloud Data Profiling.




- Practical experience building rule specifications, mappings, dictionaries, reusable DQ assets, profiling tasks, scorecards, exception management, and monitoring processes.
- Strong understanding of data quality dimensions, rule design, thresholds, controls, root-cause analysis, remediation, and data-quality KPIs.
- Proficiency in SQL for profiling, reconciliation, source validation, test-data preparation, and defect analysis.
- Experience with cloud data lakes and file-based ingestion, preferably Azure Data Lake Storage Gen2, CSV-based landing patterns, and enterprise data pipelines.
- Experience integrating IDMC with relational databases, ERP systems, cloud platforms, catalog/metadata capabilities, and downstream reporting solutions.
- Working knowledge of data governance concepts, including CDEs, business glossaries, stewardship, technical metadata, lineage, policy linkage, workflows, and data marketplaces.
- Ability to create transparent technical specifications, rule inventories, traceability documents, test evidence, deployment guides, and runbooks.

Preferred Experience
- 5+ years of overall data management, data engineering, or data quality experience, including at least 2–3 years of hands-on Informatica cloud data quality implementation.
- Experience delivering enterprise DG/DQ programs through phased or sprint-based rollouts.
- Experience working with SAP source data or SAP-to-data-lake integration patterns.
- Exposure to Informatica Cloud Data Governance and Catalog, metadata scanning, lineage, workflow, and marketplace capabilities.
- Experience supporting Power BI or other DQ monitoring dashboards.
- Experience in energy, petrochemicals, manufacturing, or similarly complex regulated environments is an advantage.

📌 Informatica IDMC Data Quality Engineer (Bengaluru)
🏢 Innova ESI
📍 Bengaluru