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Ubique Systems · Paris, Île-de-France, France

Data Architect (AWS)

seniorcontractPosted 3 days ago
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Stack mentioned

awsgdpretldatabricksunitymlflows3redshiftoauthobservabilityapache-kafkaapache-airflowdbtragllmagentic-ailangchainllamaindexcybersecuritycryptography

Duration of Contract: 12 months + Possible Extension

Languages: English + French (At least level B2)

KEY RESPONSIBILITIES

1. Data Architecture & Governance

- Design and evolve the target data architecture (lakes, lakehouses, meshes) in alignment with the IT strategy.

- Lead and drive data governance: mastership, quality, lineage, and cataloging.

- Define data management policies: lifecycle, retention, security, and GDPR/regulatory compliance.

- Produce architecture deliverables compliant with the TOGAF framework (Architecture Vision, Data Architecture, Solution Building Blocks).

- Maintain alignment with enterprise architecture and business object reference models.

2. Platform, Engineering & Integration

- Design and oversee data pipelines (ingestion, transformation, orchestration, exposure).

- Architect solutions using Databricks (Delta Lake, Unity Catalog, MLflow, DLT) and AWS (S3, Glue, Redshift, EMR, Lake Formation, Step Functions, EventBridge).

- Define integration strategies with business source systems: SAP (RFC / ABAP / ODP / BTP), Salesforce (Commerce Cloud, Data Cloud, SOQL/Bulk APIs), Kaluza, Oracle, and industry-specific ERPs.

- Support the API Management strategy: API Gateway design (AWS API Gateway, Kong, Apigee), security policies (OAuth2, JWT, mTLS), versioning, throttling, developer portals, and API observability.

- Support real-time replication and synchronization operations: Oracle GoldenGate (CDC, transaction log capture, multi-target replication), Kafka Connect, Debezium.

- Support technology selection: formats (Parquet, Delta, Iceberg), orchestration (Airflow, dbt, Spark), and storage (object, columnar, vector).

- Ensure the scalability, reliability, and observability of data infrastructure (DataOps, SLAs, alerting).

3. Platform Migration & Target Applications

- Support data platform migrations: legacy to Lakehouse/Data Mesh, on-premise to cloud, single-cloud to multi-cloud.

- Define application migration strategies (Rehost/Replatform/Refactor/Replace) and their impact on data flows.

- Develop migration architecture documentation: analysis of current state, dependency mapping, target roadmap, cutover plan, and go/no-go criteria.

- Oversee data migration operations: extraction, transformation, and loading (ETL/ELT) from SAP (via Theobald Xtract, ODP), Oracle databases (via GoldenGate), Salesforce CRM (Bulk API v2), and Kaluza systems.

- Manage coexistence and parallel-run periods: bidirectional synchronization, transitional mastership rules, and validation of migrated data integrity.

- Document lessons learned and build a library of reusable migration patterns.

4. AI & GenAI

- Define architecture for AI/ML and GenAI solutions (feature stores, model registries, serving layers, RAG, agents).

- Integrate LLMs into business processes securely, traceably, and explainably (EU AI Act Article 14).

- Scope AI use cases with business teams: feasibility, architecture, required data, and risk assessment.

- Contribute to building a semantic and decision-support layer atop information systems.

- Actively monitor developments in LLMs, multimodal AI, AI agents, and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel).

5. Data Cybersecurity & Compliance

- Define and enforce data security principles: encryption (at-rest/in-transit), secrets management (AWS Secrets Manager, Vault), fine-grained access control (RBAC/ABAC), IAM.

- Integrate security requirements into data pipelines from the design stage (Security by Design, Zero Trust Data Architecture).

- Define data classification policies: sensitive data, PII, financial data, trade secrets.

- Collaborate with CISO/SOC teams on audits, risk assessments (EBIOS RM, ISO 27005), and remediation plans.

- Ensure compliance with GDPR, NIS2, DORA (financial/energy sectors), and the AI Act—translating these into concrete architectural constraints.

- Drive strategies for masking, anonymizing, and tokenizing sensitive data in non-production environments.

- Systematize security reviews for exposed APIs (OWASP API Top 10, rate limiting, audit logs, anomaly detection).

6. Leadership & Cross-Functional Influence

- Guide Data Engineering, Analytics, and product teams in applying architectural standards.

- Participate in architecture committees and governance bodies (Architecture Review Board).

- Draft scoping documents, ADRs (Architecture Decision Records), and technical standards/guidelines.

- Act as an advisor and communicate complex concepts clearly to business units and executive management.

- Mentor junior Data Engineers and Data Analysts in mastering architectural patterns.

SKILLS

- Comfortable handling complex problems in a changing environment

- Agile

- Communication skills (written and verbal), assertiveness

- IT component architecture

- Software architecture, design patterns

- Data Management Systems

- Databricks

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