Sr. Staff Data Engineer - IT
Eaton · Pune Division, Maharashtra, India
- On site
- Full-time
- $150,000 / year
- Pune Division, Maharashtra, India
Job highlights
- Lead Finance Data Hub architecture.
- Design semantic models for analytics.
- Implement data mesh and lakehouse.
- Ensure data governance and compliance.
- Drive AI data readiness.
About the role
About the Role
We’re hiring a Senior Data Architect to lead the Finance Data Hub—designing the blueprint and standards for finance data assets across Snowflake, ADF, and Power BI. You’ll operationalize our data mesh with a medallion lakehouse, deliver robust semantic models for Commercial Analytics, Core Finance (AP/AR/GL/FA), support a breadth of partnering data domains across Eaton, and embed governance and SOX‑ready controls so Finance can trust, scale, and automate decisions.Key Responsibilities
- Own the end to end data architecture roadmap for our Snowflake centric Finance Data Hub and medallion/lakehouse patterns—aligning enterprise (bronze/silver) and domain (gold) layers for scale, reuse, and velocity.
- Design and govern the semantic layer (enterprise curated datasets, star schemas, RLS) that delivers a single version of truth for analytics in Power BI; codify standards and deployment practices.
- Assess application/data platform architecture choices: decide sourcing patterns, security rules (RBAC/RLS), privacy constraints, and data residency controls in partnership with platform/security teams.
- Establish repeatable ingestion & transformation patterns with Azure Data Factory and Snowflake (orchestration, environments, naming, CI/CD), and champion DataOps guardrails.
- Assess high level data architecture from context: translate objectives into conceptual entities (e.g., customer invoices, customer master, finance master data like site and accounts) and drive a fit for purpose target state.
- 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.
Key Skills/Competency
- Data Architecture
- Finance Data Hub
- Snowflake
- Azure Data Factory (ADF)
- Power BI
- Data Mesh
- Medallion Lakehouse
- Data Governance
- SOX Compliance
- AI Data Readiness
Skills & topics
- Data Architect
- Senior Data Engineer
- Finance Data
- Snowflake
- Azure Data Factory
- Power BI
- Data Mesh
- Lakehouse
- Data Governance
- SOX Compliance
- Eaton
- Data Modeling
- ETL
- ELT
How to get hired
- Tailor your resume: Highlight experience with Snowflake, ADF, Power BI, and finance data assets.
- Showcase architecture skills: Emphasize your experience with data mesh, medallion lakehouse, and semantic modeling.
- Quantify achievements: Provide examples of delivering scalable, reliable, and cost-optimized data solutions.
- Demonstrate leadership: Mention experience mentoring teams and influencing stakeholders.
- Prepare for technical questions: Be ready to discuss data modeling, ETL/ELT processes, and governance strategies.
Technical preparation
Master Snowflake's performance optimization techniques.,Practice designing and implementing ADF pipelines.,Build complex Power BI semantic models.,Review data mesh and lakehouse concepts.
Behavioral questions
Describe a complex data architecture you designed.,How do you ensure data governance and compliance?,How do you mentor junior data professionals?,Explain how you align technical solutions to business needs.
Frequently asked questions
- What are the key technologies for the Senior Data Architect role at Eaton?
- The Senior Data Architect role at Eaton heavily utilizes Snowflake, Azure Data Factory (ADF), and Power BI. Experience with data mesh architecture, medallion lakehouse patterns, and dimensional modeling is also crucial. Familiarity with data governance, SOX compliance, and AI data readiness is expected.
- What experience level is required for the Senior Data Architect position at Eaton?
- Eaton requires a Bachelor's degree in a relevant field or equivalent experience, along with 8-10 years of data architecture/engineering experience, specifically in delivering finance-grade data assets. At least 5 years of dimensional modeling and ELT/ETL experience, and 3+ years hands-on with Snowflake, ADF, and Power BI at an enterprise scale are necessary.
- What does 'operationalize our data mesh' mean for this role?
- Operationalizing the data mesh means implementing and managing the principles of domain ownership and federated governance within the Finance Data Hub. This involves ensuring data products are discoverable, trustworthy, and accessible by their intended users, aligning with the overall data mesh strategy at Eaton.
- How important is finance domain knowledge for this Senior Data Architect role?
- Finance domain fluency is very important. The role requires understanding finance outcomes (like DSO reduction), conceptual data models for finance entities (invoices, customer master), and aligning stakeholders around finance-specific timelines, reconciliations, and metric definitions. Experience with AP/AR/GL/FA data is essential.
- What are the expectations for data governance and compliance in this role?
- This role is responsible for advancing federated data governance and quality, including CDE identification, DQ rules, scorecards, lineage, and catalog practices. Embedding SOX-ready controls and ensuring security/compliance by design (RBAC/RLS, encryption) are critical components of the Senior Data Architect's responsibilities.
- How can I best highlight my qualifications for the Senior Data Architect job at Eaton?
- To best highlight your qualifications, tailor your resume to emphasize your experience with Snowflake, ADF, Power BI, and finance data assets. Showcase your expertise in data mesh, medallion lakehouse, and semantic modeling. Quantify your achievements in delivering scalable data solutions and mention any leadership or mentoring experience.
- What is the expected work arrangement for this Senior Data Architect role?
- While the job description does not explicitly state the work arrangement, roles of this seniority level at large companies like Eaton often offer hybrid or remote options. It is recommended to clarify this during the application or interview process.