Job Summary
"Senior data engineer-IDMC for Data Quality Team /IDMC Data Quality / Data Engineering consultant. 1. Key Responsibilities:- • Develop IDMC CDI mappings and Taskflows against approved design documents — including the DQ evaluation mapping and the DQ orchestration Taskflow (nested parallel/sequential Iterator pattern). Depending on the validated approach, implement rule evaluation either as parameterised source SQL with embedded rule expressions (CDI-only) or as CDQ assets — rule specifications, maplets, and dictionary-based validations — integrated into CDI mappings • Build and maintain SQL Server database objects — control tables, rule library, error fact tables, staging tables — and write production-quality T-SQL for SQL tasks within Taskflows (audit logging, dynamic SQL assembly, watermark logic, dimension scoring) • Populate and validate the DQ rule library — translating quality rules into executable rule definitions across quality dimensions (Completeness, Validity, Consistency, Accuracy, Uniqueness, Timeliness) in whichever form the validated approach requires (T-SQL CASE expressions or CDQ rule specifications) • Execute unit testing, QA integration testing, and support production deployment across all three frameworks • Work in a paired development model with the IPS Lead Developer — actively absorbing platform knowledge, patterns, and IDMC best practices • Participate in sprint-end walkthroughs and formal knowledge transfer sessions; contribute to implementation documentation • Demonstrate independent capability by engagement end — able to add a new source connection, register a new DQ rule, and debug a failed run using the audit log without IPS support 2. Required Skills and Experiences: - Must have: • 7+ years hands-on data engineering / ETL development experience in enterprise environments • Equal and demonstrated proficiency in both IDMC CDI and IDMC CDQ — this is a dual-capability role: • CDI: mappings, Taskflows, parameter sets, runtime parameter overrides, dynamic field propagation, generic/reusable mapping patterns delivered in production • CDQ: rule specifications, maplets, cleanse/parse/verifier assets, dictionary-based validations, and binding CDQ assets to CDI mappings delivered in production • Familiarity with the April 2026 Unified Data Quality capability (DQ assets created directly within Data Integration) is a strong advantage • Advanced SQL / T-SQL — complex queries, dynamic SQL, stored procedure patterns, performance-aware query design on SQL Server • Data Quality domain understanding — quality dimensions, rule-based validation, error capture and scoring concepts • Experience working against formal design documentation with design authority governance • Comfortable in a paired / mentored development model — receptive to knowledge transfer and able to work alongside a senior external lead Nice to have: • Power BI development experience — dataset design, DAX measures, Row Level Security — useful for liaising with the Power BI track and understanding how DQ Framework output (dimension scores, error detail) will ultimately be consumed downstream • Databricks or Azure Synapse as target platforms; ABFS / ADLS familiarity • Azure fundamentals — AD groups, Key Vault, service principals • Experience in metadata-driven / control-table-driven framework builds • Power BI data model awareness (helpful for the dashboard track, not required) • Automotive or manufacturing industry background 3. Profile attributes:- • Self-sufficient developer who can take a designed component and deliver it with limited supervision • Detail-oriented — this programme has formal review gates, source control discipline, and design sign-off requirements • Strong communicator in English — daily collaboration with IPS, Volvo Technical Lead, and Data Architect • Genuinely motivated to learn — the engagement is deliberately structured to build lasting
Key Responsibilities
3. Profile attributes:-
• Self-sufficient developer who can take a designed component and deliver it with limited supervision
• Detail-oriented — this programme has formal review gates, source control discipline, and design sign-off requirements
• Strong communicator in English — daily collaboration with IPS, Volvo Technical Lead, and Data Architect
• Genuinely motivated to learn — the engagement is deliberately structured to build lasting IDMC capability, and the consultant is one of the primary recipients of that investment
Role: Senior Data Engineer – IDMC / Data Quality
We are looking for a Senior Data Engineer with strong hands-on experience in Informatica IDMC CDI & CDQ, SQL, and modern Azure/Databricks data platforms. The role involves developing a metadata-driven Data Quality framework, building CDI mappings and Taskflows, implementing CDQ rules, and integrating data pipelines with Azure and Databricks.
Tech Stack:
• Informatica IDMC: CDI, CDQ, Mappings, Taskflows, Parameter Sets
• Data Quality: Rule Specifications, Maplets, Dictionaries, DQ Dimensions & Scoring
• Database: SQL Server, T-SQL, Stored Procedures, Dynamic SQL
• Azure: ADLS/ABFS, Azure Data Factory, Key Vault, Entra ID/Service Principals
• Databricks: PySpark, Spark, Delta Lake, Databricks Workflows
• Others: Power BI, Git/DevOps, Metadata/Control-table driven frameworks
Key Skills:
• 7+ years of hands-on Data Engineering/ETL experience
• Strong IDMC CDI + CDQ production experience
• Advanced SQL/T-SQL and data quality concepts
• Experience building reusable and metadata-driven frameworks
• Azure and Databricks data engineering experience
• Strong debugging, testing and production deployment skills
• Ability to work independently and collaborate with architects/technical leads
• Good communication and documentation skills
Ideal candidate:
A hands-on Data Engineer who combines IDMC Data Integration + Data Quality expertise with Azure and Databricks experience and can independently develop, test, troubleshoot and deploy enterprise-grade data pipelines and DQ solutions.
IDMC CDI and IDMC CDQ