Data Engineer
Reads like a Data Governance role: data quality and governance.
Warsaw Domaniewska, MZ, PL, 02-672
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild and run a Finance data quality framework with validation and reconciliation controls
Design and maintain scalable semantic models and star-schema models for reporting
Reconcile data between the Data Cloud, ERP systems and official financial results
Develop and optimize Databricks ingestion pipelines and troubleshoot their issues
Document SOX 302 and 404 data controls and support audits with evidence and lineage
From the employer’s posting
Build and operate a robust Finance data quality framework across the data cloud
Design, build, and maintain scalable semantic models for reporting and analytics
Reconcile data between the Data Cloud, ERP systems, and official financial results
Develop, maintain, and optimize ingestion pipelines using Databricks
Document and maintain SOX 302 & 404 data controls
Education & alternatives
Your skills and experience include: - Bachelor’s or Master’s degree in Data Engineering, Computer Science, Finance, or related field - Experience in data engineering, ideally within Finance or regulated environments
Tools in this posting
- Python
- SQL
- Databricks
- Delta Lake
- Oracle
- Power BI
- SAP
Source — Tool mentions in context
- ERP knowledge (SAP, Oracle, consolidation systems) - Python for automation and testing - Experience supporting Finance transformation or GBS environments
- Experience in data engineering, ideally within Finance or regulated environments - Strong hands‑on experience with Databricks, SQL, Delta Lake, and Lakehouse architecture - Proficiency in Power BI semantic models (tabular models, DAX, modeling best practices)
- Ensure Finance data pipelines meet SOX, compliance, and audit requirements 2. Semantic Model Development (Databricks & Power BI) - Design, build, and maintain scalable semantic models for reporting and analytics
- Design, build, and maintain scalable semantic models for reporting and analytics - Create optimized curated Finance layers, Delta tables, and datasets in Databricks - Engineer robust dimensional and star‑schema models aligned to Finance processes
4. Data Pipeline Engineering - Develop, maintain, and optimize ingestion pipelines using Databricks - Ensure pipelines are scalable, performant, and aligned with engineering best practices
- Exposure to MDM, data cataloguing, and governance tooling - ERP knowledge (SAP, Oracle, consolidation systems) - Python for automation and testing
- Strong hands‑on experience with Databricks, SQL, Delta Lake, and Lakehouse architecture - Proficiency in Power BI semantic models (tabular models, DAX, modeling best practices) - Understanding of Finance processes (GL, FP&A, actuals, budgets, forecasts)
About Coty
At Coty, we celebrate diversity, fearless kindness, and bold thinking—creating an inclusive workplace where everyone can be their authentic self.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 23, 2026 · 6 days ago
- Recorded sightings
- 94
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
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- Check the listed location, eligibility and core experience before starting.
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Job description
FINANCE DATA ENGINEER
FINANCE / DATA & ANALYTICS
As our Finance Data Engineer, you will play a critical role in building a trusted, high‑quality Finance data ecosystem that enables analytics, reporting, and AI‑driven decision‑making, helping Finance teams rely on a single, governed source of truth.
THE ROLE
OPTIMIZE, ENABLE, INNOVATE!
As our Finance Data Engineer, you are responsible for designing and maintaining high‑quality, SOX‑compliant Finance data assets within Coty’s Data Cloud. You will engineer scalable semantic models, ensure data accuracy and reconciliation, and partner closely with Finance, Reporting, and IT teams to deliver trusted, audit‑ready data for global decision‑making.
YOUR MAIN RESPONSIBILITIES
1. Data Quality Ownership & Governance
- Build and operate a robust Finance data quality framework across the data cloud
- Define and implement validation, anomaly detection, reconciliations, and monitoring controls
- Partner with Finance SMEs to define data standards, business rules, and master data
- Lead root‑cause analysis and remediation of data quality issues
- Ensure Finance data pipelines meet SOX, compliance, and audit requirements
2. Semantic Model Development (Databricks & Power BI)
- Design, build, and maintain scalable semantic models for reporting and analytics
- Create optimized curated Finance layers, Delta tables, and datasets in Databricks
- Engineer robust dimensional and star‑schema models aligned to Finance processes
- Collaborate with Finance analysts to ensure usability, documentation, and business alignment
- Implement role‑based security, lineage, and data catalog integration
3. Data Reconciliation & SOX Compliance
- Reconcile data between the Data Cloud, ERP systems, and official financial results
- Build automated reconciliation checks across transformation layers
- Document and maintain SOX 302 & 404 data controls
- Support internal and external audits with evidence, lineage, and control walkthroughs
4. Data Pipeline Engineering
- Develop, maintain, and optimize ingestion pipelines using Databricks
- Ensure pipelines are scalable, performant, and aligned with engineering best practices
- Monitor pipeline health, troubleshoot issues, and drive enhancements
- Partner with IT and platform teams to ensure high availability of Finance data assets
5. Cross‑Functional Collaboration
- Work closely with FP&A, Commercial Finance, Supply Chain Finance, and Controlling teams
- Translate reporting and analytical requirements into technical data solutions
- Partner with Data Governance, Security, and Platform teams on standards and architecture
- Enable self‑service analytics through certified, high‑quality datasets
YOU ARE A COTY FIT
As a data‑driven and detail‑oriented engineer, you thrive at the intersection of Finance, data, and technology.
Your skills and experience include:
- Bachelor’s or Master’s degree in Data Engineering, Computer Science, Finance, or related field
- Experience in data engineering, ideally within Finance or regulated environments
- Strong hands‑on experience with Databricks, SQL, Delta Lake, and Lakehouse architecture
- Proficiency in Power BI semantic models (tabular models, DAX, modeling best practices)
- Understanding of Finance processes (GL, FP&A, actuals, budgets, forecasts)
- Experience with data quality frameworks, reconciliations, and lineage documentation
- Knowledge of SOX controls, audit requirements, and compliance‑driven data management
- Strong analytical mindset and proactive, problem‑solving attitude
Nice to have:
- Experience in enterprise‑scale Data & AI platforms
- Exposure to MDM, data cataloguing, and governance tooling
- ERP knowledge (SAP, Oracle, consolidation systems)
- Python for automation and testing
- Experience supporting Finance transformation or GBS environments
WHAT WE OFFER
This role offers the opportunity to shape Finance’s data foundation from the ground up.
- Key role in building Finance’s single source of truth
- High visibility and collaboration with global Finance and IT stakeholders
- Exposure to modern data, analytics, and AI technologies
- International, transformation‑driven environment
- Hybrid working model and flexible ways of working
ABOUT US
Our people make us who we are. At Coty, we celebrate diversity, fearless kindness, and bold thinking—creating an inclusive workplace where everyone can be their authentic self.
Source details
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- Pay
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- Location & working pattern
Warsaw Domaniewska, MZ, PL, 02-672
- International, transformation‑driven environment - Hybrid working model and flexible ways of working ABOUT US
- Work authorization
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