Senior Specialist IT - Data Engineering

• Advance federated data governance and quality with domain owners and stewards-CDE identification, DQ rules, scorecards, lineage, and catalog practices that drive trust.
• Raise our AI data readiness-ensure data products include the metadata, quality, lineage, and controls AI requires; align with emerging AI governance and risk processes.
• Engineer for performance, reliability, and cost-optimize Snowflake warehouses, refresh/gateway health, and observability for >99% availability across the analytics estate.
• Embed security and compliance by design-RBAC/RLS, encryption, least privilege, and cloud security controls across data stores, pipelines, and BI surface.
• Coach and uplift talent-mentor architects, engineers, and stewards; cultivate reusable patterns, reference implementations, and strong "data as an asset" practices.
• Operationalize CI/CD for data & BI-govern branching, releases, and deployment pipelines for Snowflake/Power BI; drive automated reconciliation and validation.
• Partner across platform & analytics teams to harmonize ingestion/lakehouse with reporting and ML, accelerating domain roadmaps and cross domain reuse.
• Co create test strategy and exit criteria with the Product Owner; define data/semantic validation and performance thresholds needed for release and sign off.
• Joint design sign off: partner with DF&I techno functional leadership to review and sign off the detailed technical design and data model for FDH assets.

Qualifications:

Bachelor's in Computer Science, Data/Information Systems, Engineering, Mathematics, or related field (or equivalent experience).
8-10 years in data architecture/engineering with a record of shipping finance-grade data assets and semantic models.
5+ years dimensional modeling and ELT/ETL for analytical workloads; 3+ years hands-on with Snowflake, ADF, and Power BI at enterprise scale.

Skills:

• Architectures & Patterns: Data mesh (domain ownership, federated governance) and medallion lakehouse (bronze/silver/gold) applied to Finance use cases.
• Snowflake (Finance focus): warehouse optimization, materialized views/search optimization, secure data sharing, and workload segregation for close windows.
• ADF & DataOps: standardized pipelines, environment promotion, CI/CD options for data; defensible naming and metadata capture for auditability.
• Semantic Layer & BI: Power BI deployment pipelines, DAX standards, Tabular Editor/DAX Studio usage, and scalable RLS patterns for sensitive finance hierarchies.
• Modeling Standards: domain agnostic bronze/silver guidance and domain aligned finance gold (facts/dims for AP, AR, GL, FA, Intercompany); conformed dimensions and metric definitions.
• Governance & MDM: CDE identification, glossary/lineage, DQ rules & scorecards; integration with finance hierarchies/MDM and stewardship councils.
• Security/Compliance: RBAC, RLS, encryption and Azure security controls; awareness of SOX and data privacy impacts on finance reporting pipelines.
• Testing & Readiness: automated reconciliation Snowflake→Power BI, SIT/UAT for KPI sign off, and performance testing for semantic models.
• AI Data Readiness & Governance: AI risk checkpoints, data policy as code direction, and regulatory awareness embedded in asset lifecycle.
• Business-anchored architecture: connects high-level finance outcomes (e.g., DSO reduction) to conceptual data models and target state architectures (invoices, customer master, finance master data).
• Standards stewardship: demonstrated ability to apply and contribute to enterprise data mesh standards/playbooks, surfacing reusable patterns and guardrails."
• Finance domain fluency communicates trade offs in plain language; aligns stakeholders around close timelines, reconciliations, and metric definitions.
• Systems & lifecycle thinking connects ingestion→modeling→semantic→consumption with documentation and enablement that auditors and analyst's trust.
• Leadership & influence: mentors engineers/stewards; builds consensus across Finance, Platform, and Governance forums.
• Outcome orientation: delivers measurable gains in reliability, quality, adoption, and cost within FDH.
• Collaborative orchestration: not the expert in every domain, but consistently brings the right people together (DF&I product owner, Architecture Guild, IDM Finance BU team, platform/security, stewards) to move from intent → design → sign off → release.

Client-provided location(s): Pune, India

Job ID: Eaton-57338Pune

Employment Type: OTHER

Posted: 2026-01-23T18:38:36