Data Architect
- Full-time
Company Description
Inetum is a European leader in digital services, supporting organizations as they navigate continuous technological change. The company helps clients accelerate their digital transformation through a broad portfolio that includes consulting, application services, digital engineering, cloud, cybersecurity, platforms, and infrastructure services
Job Description
We are looking for a mid- to senior level Data Architect & Tooling Specialist whose primary mission is to maintain, evolve, and steward our existing data platform. That is a hands on architect who will design, implement, and operate the tooling ecosystem that guarantees the reliability, observability, and compliance of our data platform.
The role is heavily weighted toward metadata management, data quality frameworks, CI/CD pipelines, and governance dashboards.
The success will be measured by number of data quality incidents, the clarity and completeness of our data catalog, the robustness of governance processes, the adoption of data quality and self-service tools, and the overall transparency of data flows to business users
Main Tasks:
- Metadata & Semantic Layer, which consists on developing and maintaining the data product catalog, lineage, and metadata standards
- Design, implement, and continuously improve a centralized metadata repository
- Define and enforce semantic models, particularly business vocabularies, canonical data entities and logical data contracts that translate raw tables into understandable business objects
- Maintain lineage graphs that are automatically refreshed on each pipeline run
- Coordinate efforts with wider bank initiatives related to metadata
- Governance, Transparency & Compliance: Provide transparent dashboards for data lineage, access logs, and data quality health that are consumable by business users, auditors, and regulators
- Lead quarterly data governance reviews, focusing on data ownership and access
- Integrate with broader data governance initiatives
- Tooling & Automation, which consists on implementing self service data product templates that embed semantic metadata automatically
- Introduce observability for data pipelines and lineage updates
- Collaboration & Knowledge Sharing, which involves working with domain owners to capture business definitions and map them to technical entities
- Conduct regular sessions on metadata best practices
- Mentor engineers on embedding semantic annotations
Qualifications
Technical Skills:
- Observability: Prometheus, Grafana, OpenTelemetry, or equivalent for pipeline monitoring
- Tooling & Automation: CI/CD, dbt or similar, Airflow / Dagster / Prefect or similar
- Metadata Management: Proven experience building and maintaining a data catalog/lineage system (DataHub, Amundsen, Collibra, Alation or similar)
- Semantic Modeling: Ability to design business level vocabularies, canonical data models, and data contracts; experience with Data Mesh or other domain oriented data products is a plus. Experience with formal verification is a huge plus
- AI Assisted Data Quality: Ideally hands on experience with ML based profiling tools (Great Expectations + ML, Monte Carlo, Datafold, Bigeye and such) or the ability to develop custom models (e.g., using Python) for anomaly detection
Language Skills:
- English - Expert
- Python - Expert
- SQL - Expert
- Shell / Bash - Practice
- Java / Scala or similar - Practice
Soft Skills:
- Focusing on targets
- Ability to work with team
Additional Information