Your area of work:
As a Data Architect at Clearstream Securities Services, you will play a key role in driving our digital transformation by shaping the data architecture that underpins strategic initiatives such as Data & AI, the D7 digital securities platform, the modernization of our Digital CSD, and our cloud adoption journey. Your work will ensure that Clearstream’s data ecosystem is secure, scalable, and future-ready, enabling advanced analytics, regulatory compliance, and innovative services for global financial markets. By defining enterprise standards and collaborating across domains, you will help position Clearstream as a leader in digital finance and data excellence.
Your responsibilities:- Define the target-state cloud data architecture (Lakehouse) across BI, analytics, and ML—including reference architectures, patterns, and guardrails.
- Lead domain-driven and Data Mesh architecture: curate federated data product standards, contracts, and interoperability guidelines.
- Establish architecture decision records (ADRs) and technology roadmaps (near/mid/long term), aligning with enterprise data strategy and regulatory requirements.
- Act as a trusted advisor to data scientists, analysts, and business product teams; unlock self-service patterns and reuse.
- Lead onboarding, training, and enablement programs to scale platform and catalog adoption; raise data literacy across domains.
- Mentor engineers and stewards; foster a culture of automation, reliability, and measurable outcomes.
- Guide the design and configuration of Atlan workspaces, clusters, compute policies, and libraries; ensure high availability, scalability, and cost efficiency.
- Own enterprise metadata strategy—ingestion, enrichment, and stewardship—leveraging Atlan (or equivalent) for catalog, lineage, glossary, and data contracts.
- Define data quality frameworks (profiling, rules, SLAs, monitoring) using solutions like Soda/Great Expectations; embed DQ controls into pipelines.
- Establish critical data element (CDE) standards, certification workflows, and KPIs; publish management reporting on catalog adoption and DQ outcomes.
- 8–12+ years in data architecture/engineering within cloud big data platforms (GCP preferred), including enterprise and regulated environments.
- Proven leadership in Databricks/Spark, Lakehouse architectures, and operationalizing Unity Catalog at scale.
- Hands-on track record with metadata/catalog platforms (Atlan/Collibra) and data quality frameworks (Soda/Great Expectations), including enterprise rollout and adoption.
- Demonstrated success aligning IT, business, compliance, and security to implement governed, high-quality data solutions.
- Deep understanding of data modeling, data contracts, DQ SLAs, lineage, privacy/security, and observability (e.g., Azure Monitor/Datadog).
- Working knowledge of ML lifecycle (MLflow, feature stores) and semantic/metrics layers for analytics products.
- Executive-level communication, stakeholder engagement, and influence; comfortable with board-level reporting and audit dialogue.
- Strong facilitator and coach; able to drive consensus across diverse technical and business teams.
- Fluent in English; additional language skills are a plus.
- Certifications (preferred)
- Azure Data Engineer/Architect; Databricks Data Engineer Professional/Architect; TOGAF; CDMP (DAMA); Security/Compliance certifications are advantageous.
