BI Data Engineer

Tata Consultancy Services; Brussel Hoofdstad; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Tata Consultancy Services in Belgium seeks a senior BI/EDW specialist to design and maintain enterprise data warehouses and BI solutions. You will craft data lakehouse architectures for cloud, on-prem, and hybrid environments, ensuring security, residency, and governance across pipelines, models, and dashboards.

The role emphasizes data quality, performance, and self-service analytics with strong collaboration across multicultural teams and stakeholders.

Qualifications

• Experience with enterprise data warehouses and data lakehouse designs.
• Strong SQL and data modelling skills for analytics and reporting.
• Familiarity with data governance and security across on-prem and cloud

Responsabilités

• Create and maintain Enterprise Data Warehouses (EDW) and BI Solutions (Data Lakes/Data Lakehouses).
• Design BI architectures for cloud, on-prem, and hybrid environments with data residency in mind.
• Develop data pipelines, validation tests, and governance artifacts (dictionaries, lineage).

Connaissances

EDW design

Data lakehouse architectures

Data governance

SQL

Cloud BI architectures

Multicultural collaboration

Formation

Microsoft Data Analyst Associate

Amazon Certified Data Analytics Specialty

Outils

Power BI

Tableau

Qlik

Informatica

Talend

dbt

Azure Data Factory

Delta Lake

Azure Synapse

Snowflake

AWS Redshift

Collibra

Alation

Azure Purview

Kafka

Debezium

Description du poste

Employment Type: Full-time

Nature of the tasks

• Create and maintain Enterprise Data Warehouses (EDW) and complex Business Intelligence Solutions (Data Lakes / Data Lakehouses).
• Design modern Business Intelligence (BI) architectures (e.g., data lakehouse) for cloud, on premises, and hybrid environments, ensuring compliance with security and data residency requirements.
• Gather and analyse business requirements specifically for data pipelines, storage, and reporting solutions.
• Design and implement modern Extract, Transform, Load / Extract, Load, Transform (ETL/ELT) processes and orchestration workflows, incorporating data contracts and schema evolution management.
• Implement and manage data virtualization layers to provide unified access to heterogeneous data sources while optimizing performance and security.
• Design and implement data models (e.g., dimensional modelling) to support reporting and analytics, ensuring alignment with business requirements.
• Design and build reporting and analytics applications, creating dashboards, KPIs, and self-service BI tools that deliver actionable insights to business stakeholders.
• Design and optimize the physical database schema, including indexing, partitioning, and storage strategies, to balance performance, cost, and maintainability.
• Conduct ongoing database performance analysis, tuning queries, optimizing resource utilization, and ensuring SLAs for latency and throughput are met.
• Design and implement data quality frameworks and health monitoring processes that include data observability (lineage, freshness) and defined Service Level Agreements / Service Level Objectives (SLAs/SLOs).
• Define and execute test programs for BI solutions, including data validation, regression tests, contract tests, and automated pipelines integrated into CI/CD.
• Produce and maintain technical documentation (data dictionaries, lineage, design specifications, runbooks) to support transparency, governance, and audit readiness.
• Perform deployment and configuration of BI systems and platforms, applying infrastructure-as-code, version control, and environment management practices.
• Govern the BI semantic layer (KPIs, metrics catalog, naming conventions, row-level security) to ensure consistency and trusted insights.
• Manage access controls and data security within BI platforms in alignment with GDPR and internal data protection policies.
• Optimize cost and performance of BI platforms and warehouses (partitioning, caching, clustering, query optimization, resource scaling).
• Define and enforce data lineage and stewardship practices, ensuring transparency, auditability, and compliance.
• Enable self-service BI capabilities for business users through curated datasets, certified reports, and training/support.

Specific expertise and technologies

• Knowledge of enterprise data warehouse design and architecture, including dimensional modelling and star/snowflake schema design.
• Knowledge of data lake and lakehouse design patterns (e.g., Delta Lake, Apache Iceberg) to support large-scale analytics.
• Excellent knowledge of relational database systems applied to data warehouse.
• Knowledge of non-relational databases (e.g., MongoDB, Cassandra, Hadoop HBase) for handling unstructured and semi-structured data.
• Excellent knowledge of SQL.
• Knowledge of BI reporting and analytics tools (e.g., Power BI, Tableau, Qlik) for enterprise dashboards and self-service analytics.
• Knowledge of ETL and ELT tools (e.g., Informatica, Talend, dbt, Azure Data Factory) to manage enterprise data pipelines.
• Knowledge of modelling tools (e.g., ERwin, SAP PowerDesigner, ArchiMate for data flows) to design logical and physical data models.
• Knowledge of OLAP technologies (e.g., SSAS, Essbase) and data mining tools (e.g., SAS Enterprise Miner, RapidMiner).
• Knowledge of near real-time data ingestion and change data capture (CDC) technologies (e.g., Kafka, Debezium, GoldenGate).
• Knowledge of cloud BI architectures (e.g., Azure Synapse, Snowflake, AWS Redshift) to enable scalable analytics.
• Knowledge of data governance and cataloguing practices (e.g., Collibra, Alation, Azure Purview) to ensure trusted data assets.
• Knowledge of data observability practices (e.g., freshness, lineage, anomaly detection) to monitor and assure pipeline quality.

Minimum level of expertise

• Normal

Certification and/or Standards

Optional: One of the following or an equivalent certification:

• Microsoft Data Analyst Associate
• Amazon Certified Data Analytics Specialty

Skills

• Ability to apply rigour and consistency in BI development practices.
• Ability to work in multi-cultural environment.
• Ability to participate in multilingual meetings.
• Ability to understand, speak and write English; one of French or Dutch is a plus
• Talent for building relationships and adapting communication to the audience.
• Ability to work in a team as well as autonomously.
• Results-oriented mindset, focused on delivering.