Senior Data Engineer

TUV AUSTRIA BELGIUM NV

Rotselaar, Belgium

yesterday

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

Dutch, English

Experience level

Senior

Job location

Rotselaar, Belgium

Tech stack

Artificial Intelligence

Airflow

Amazon Web Services (AWS)

Data analysis

Azure

Big Data

Google BigQuery

Cloud Computing

Information Systems

Data Architecture

Information Engineering

Data Governance

Data Integration

ETL

Data Transformation

Data Systems

Data Warehousing

Distributed Systems

Data Flow Control

Github

Python

Machine Learning

Performance Tuning

Power BI

DataOps

Azure

SQL Databases

Data Streaming

Tableau

Unstructured Data

Azure

Snowflake

Spark

Microsoft Fabric

Containerization

Data Lake

Kubernetes

Information Technology

Kafka

Cosmos DB

Machine Learning Operations

Terraform

Data Pipelines

Docker

Databricks

Job description

Data Architecture & Pipelines: Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and deliver structured and unstructured data.
Data Governance & Quality: Implement governance frameworks, data catalogs, and quality assurance processes to ensure compliance, integrity, and security of all data assets.
Data Integration & Storage: Manage data lakes, warehouses, and streaming platforms; optimize storage solutions for performance and cost-efficiency.
Enable AI & Analytics: Prepare and curate datasets for machine learning and advanced analytics projects, ensuring accessibility and reliability for data scientists and AI engineers.
Performance Optimization: Monitor and optimize data workflows for speed, scalability, and resilience in cloud and on-prem environments.
Collaboration: Work closely with cross-functional teams (data scientists, software engineers, project managers) to deliver end-to-end data solutions.
Continuous Improvement: Stay updated on emerging technologies in data engineering, big data, and cloud platforms; drive adoption of best practices.
Client Interaction: Support clients in understanding data requirements, present technical solutions, and provide expertise on data-driven strategies.

Requirements

Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
Experience: 3-5 years in data engineering, big data, or data platform development.
Technical Skills:

Strong proficiency in Python and SQL; experience with distributed systems (Spark, Databricks).
Cloud Platforms: o Microsoft Azure: Azure Data Factory, Azure Data Lake Storage, Microsoft Fabric,Azure Cosmos DB. o Other Clouds: AWS (Glue, RDS, Athena, Redshift, S3), GCP (BigQuery, Dataflow).
Data Orchestration & Workflow: Airflow, Prefect, Dagster, ADF
Data transformation: dbt
Data Warehousing & Modeling: Snowflake, DuckDB, BigQuery.
Streaming & Real-Time Processing: Kafka, Azure Event Hub.
Visualization & BI: Power BI, Tableau.
Familiarity with CI/CD pipelines (Azure DevOps, GitHub Actions) and containerization (Docker, Kubernetes).
Infrastructure as Code: Terraform

Analytical Thinking: Ability to design efficient data workflows and troubleshoot complex data issues.
Communication: Clear and concise communication skills for technical and non-technical stakeholders.
Ethical Standards: Commitment to data privacy, security, and compliance with relevant regulations.
Bonus: Experience with MLOps and DataOps.
Fluency in both written and spoken Dutch and English is required.