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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect - **Company:** Tata Consultancy Services - **Location:** Brussel, Belgium - **Contract:** Permanent contract - **Skills:** Third Normal Form, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Apache HTTP Server, Automation of Tests, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Databases, Continuous Integration, Data Architecture, Data Control, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Profiling, Data Security, Data Structures, Data Stores, Data Systems, Data Vault Modeling, Disaster Recovery, Github, Graph Database, Interoperability, Key Management, PostgreSQL, Metadata, Metadata Repositories, Language Modeling, MongoDB, NoSQL, Oracle (Applications), Performance Tuning, PowerDesigner, Role-Based Access Control, Cloud Services, DataOps, SAP (Applications), SQL Databases, Data Streaming, Talend, UML, Openapi, Parquet, Datadog, Google Cloud, Azure Data Factory, Snowflake, Apache Spark, Archimate, Data Strategy, Git, Togaf, Microsoft Fabric, Data Lakes, Gitlab-ci, Debezium, Data Lineage, Collibra, Apache Flink, Cassandra, Bicep, Apache Kafka, Apache Nifi, Graphql, Spark Streaming, Data Management, Presto, Physical Data Models, Restful APIs, Terraform, Grpc, Azure Synapse Analytics, Software Version Control, Data Pipelines, Devsecops, Amazon Redshift, Databricks - **Published:** September 4, 2026 - **Apply:** https://www.adzuna.be/details/5868787870 ## About the Role * Knowledge of enterprise data architecture methods and reference models (e.g., DAMA-DMBOK, Data Mesh principles, Data Fabric patterns). * Knowledge of data modelling approaches: 3NF, dimensional/star-schema, and Data Vault 2.0; experience with modelling languages/tools (e.g., ER, UML, ArchiMate; ERwin, SAP PowerDesigner). * Experience with metadata and cataloguing platforms to govern lineage and ownership (e.g., Collibra, Alation, Azure Purview, OpenLineage). * Knowledge of data governance and quality frameworks (e.g., ISO 8000, ISO/IEC 11179), including stewardship, data domains, and controls. * Understanding of privacy, security, and compliance requirements (e.g., GDPR, ISO/IEC 27001), including encryption, key management, RBAC/ABAC, and data residency. * Experience with integration patterns and pipelines: ETL/ELT, CDC, event streaming (e.g., Kafka, Debezium) and orchestration (e.g., Airflow, Azure Data Factory, Dagster). * Knowledge of lakehouse and warehouse architectures, table/format standards (e.g., Delta Lake, Apache Iceberg, Apache Hudi) and columnar formats (e.g., Parquet). * Experience with cloud data platforms such as Azure Synapse, Databricks, Microsoft Fabric, Snowflake, and Amazon Redshift. * Knowledge of relational and NoSQL data stores and when to apply them (e.g., PostgreSQL, Oracle, MongoDB, Cassandra, time-series and graph databases). * Experience with distributed compute/query engines (e.g., Spark, Trino/Presto, Databricks SQL) for large-scale processing. * Knowledge of API and interoperability standards for data access (e.g., SQL, REST, GraphQL, gRPC, OpenAPI/AsyncAPI specifications). * Experience with semantic/metrics layers and BI modelling (e.g., dbt Semantic Layer, LookML, MetricFlow) to standardize KPIs. * Understanding of master and reference data management practices and tooling (e.g., Informatica MDM, Semarchy, Reltio). * Experience with data quality/observability tooling and SLAs/SLOs (e.g., Great Expectations, Soda, Monte Carlo) to monitor freshness, completeness, and lineage. * Knowledge of streaming and real-time patterns (e.g., Spark Structured Streaming, Flink) and state stores (e.g., Kafka Streams). * Experience with DevSecOps/DataOps practices: version control, CI/CD for data, automated testing, and environment promotion (e.g., Git, GitHub/GitLab CI). * Knowledge of Infrastructure-as-Code and Policy-as-Code for data platforms (e.g., Terraform, Bicep, OPA) to ensure repeatable, governed deployments. * Understanding of backup/restore, disaster recovery, and retention strategies with RPO/RTO targets for data platforms. * Experience with cost and performance optimization across compute, storage, and egress (e.g., workload right-sizing, caching/partitioning, lifecycle policies). * Knowledge of collaboration and documentation practices (e.g., ADRs, C4 context for data flows, glossary/business term management). * Understanding of AI/analytics enablement: feature stores and model data needs (e.g., Feast), responsible AI data controls aligned to EU AI Act principles. Minimum Level of Expertise * Advanced Certification and/or Standards Mandatory: One of the following or an equivalent certification: * TOGAF * CDMP * DAMA-DMBoK * ISO Data Governance Standards Optional: * Cloud Data Certifications (AWS, Azure, etc.) * ITIL 4 Foundation * SAFe * Security Certifications (e.g., CCSP, CISSP) Skills * Capacity to leverage storytelling in data architecture communications. * Ability to synthesize long-term business objectives with technical feasibility to guide project vision and validate architectural decisions. * Ability to understand, speak, and write English; French is considered an additional asset. * Ability to work both independently and as part of a team. * Ability to participate in multilingual meetings. * Excellent interpersonal and communication skills. * Results-oriented mindset focused on delivering outcomes. ## Description * Develop and implement the organization's overarching data strategy, creating blueprints for data management that align with and enable key business objectives. * Translate business requirements into technical specifications and data architecture designs, ensuring the data infrastructure supports both immediate and long-term needs. * Create conceptual, logical, and physical data models (e.g., dimensional for analytics) that define data structure, relationships, and storage. * Maintain metadata repositories to ensure data accuracy, lineage, and integration, curating both technical and business metadata for clarity. * Architect solutions to integrate data from disparate sources (ERPs, CRMs) using ETL/ELT processes and tools (e.g., Apache NiFi, Talend) into a unified framework. * Build and manage streaming data pipelines (e.g., using Kafka, Spark Streaming) to support real-time analytics and decision-making. * Define and enforce data governance policies, including data quality standards, lineage tracking, access controls, and a data catalog. * Implement security protocols (encryption, RBAC) and design architectures to ensure adherence to regulations like GDPR. * Implement processes for data profiling, validation, and cleansing to ensure ongoing data accuracy, consistency, and reliability. * Evaluate and select appropriate database systems (SQL, NoSQL), cloud platforms (AWS, Azure, GCP), and tools that meet scalability and performance needs. * Architect and deploy scalable data solutions in cloud (e.g., Snowflake) or hybrid environments, optimizing for cost-efficiency. * Monitor, troubleshoot, and optimize data systems and pipelines for performance, scalability, and cost. * Work with business leaders, data engineers, and scientists to ensure the architecture meets diverse needs and bridges technical and non-technical gaps. * Mentor data teams on best practices, standards, and tools; lead data-centric projects and strategic initiatives. * Oversee the entire data lifecycle, from collection and storage to archiving and purging, ensuring data remains manageable and relevant. * Stay abreast of trends in big data, AI, and cloud computing to continuously innovate and modernize the data architecture. ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Exploring the Power of gRPC-Gateway for Writing RESTful Services](https://www.wearedevelopers.com/videos/2072-exploring-the-power-of-grpc-gateway-for-writing-restful-services) - [ChatGPT and Java: A Match Made in Heaven or Hell?](https://www.wearedevelopers.com/videos/536-chatgpt-and-java-a-match-made-in-heaven-or-hell) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Boosting OpenSearch Performance: gRPC Search in Action](https://www.wearedevelopers.com/videos/1964-boosting-opensearch-performance-grpc-search-in-action) - [Beyond UML: Making Sense of AI-Generated Code through Visual Architecture](https://www.wearedevelopers.com/videos/2102-beyond-uml-making-sense-of-ai-generated-code-through-visual-architecture) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)