DATA ARCHITECT

Ayesa Digital
Belgium
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

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
+71 more
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 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 Policy as Code 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 Stream Processing Grpc Azure Synapse Analytics Software Version Control Data Pipelines Devsecops Amazon Redshift Databricks

Job description

We are looking for a Data Architect to join our international team and contribute to the develop and implementation of the organizations 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., Optional: Cloud data certifications (AWS, Azure, etc.), ITIL 4 Foundation or SAFe, and security certifications (e.g., CCSP, CISSP).

What We Offer:

  • Prestigious projects within European institutions.
  • International, innovative, and multicultural environments.
  • Continuous support from a team of experts in EU projects.

If you are ambitious, enthusiastic, and seeking a new professional challenge in international projects with real-world impact, this is the place for you!

Requirements

  • 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, Amazon Redshift.
  • Knowledge of relational and NoSQL data stores and when to apply them (e.g., PostgreSQL/Oracle; MongoDB, Cassandra; time-series/graph).
  • 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 standardise 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., stream processing with 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 optimisation 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.

Mandatory one of the following or an equivalent certification: TOGAF, CDMP, DAMA DMBoK, and ISO data governance standards.

About the company

Ayesa Digital Brussels Region, Belgium

At Ayesa Digital, we grow with you.

Every professional in our company is essential. Thanks to their talent, we continue to expand: today, we are a global team of more than 11,000 people working toward a shared mission.

Ayesa Digital is currently participating in high-impact European Union projects designed to address major European challenges and drive science and innovation. These strategic technological initiatives stand out for their international scope and strong commitment to socially oriented results.

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