Technical Data Architect

XFactor Talent; Eindhoven; On-site; EUR 90,000 - 150,000; Full time

Job summary

XFactor Talent is seeking an experienced Lead Technical Data Architect / Data Engineer to lead the design, development, and implementation of scalable enterprise data platforms and solutions. The role requires hands-on leadership and deep expertise in data architecture, cloud platforms (AWS, Azure, GCP), ETL/ELT, data modelling, and modern analytics ecosystems.

You will collaborate with business stakeholders, architects, data scientists, and engineers to deliver reliable, high-performance data

Qualifications

• Hands-on experience leading enterprise-scale data platforms.
• Deep cloud data platform expertise (AWS/Azure/GCP).
• Strong ETL/ELT, data modelling, and governance knowledge.

Responsibilities

• Lead architecture and design of enterprise-scale data platforms and pipelines.
• Design scalable data lakes, data warehouses, lakehouses, and modern architectures.
• Define standards, patterns, frameworks, and best practices.
• Develop and optimize ETL/ELT pipelines for structured and unstructured data.
• Design data models, schemas, and dimensional models.
• Collaborate with stakeholders to translate requirements into data solutions.
• Ensure data quality, governance, security, lineage, and compliance.
• Establish CI/CD and DevOps practices for data engineering.

Skills

Python

Scala

SQL

Batch processing

Streaming

Data Lakes

Data Warehouses

Delta Lake

Databricks

Snowflake

Kafka

Kinesis

Event Hubs

ETL/ELT

Data Governance

Tools

Docker

Terraform

Git

Job description

We are looking for an experienced Lead Technical Data Architect / Data Engineer to lead the design, development, and implementation of scalable enterprise data platforms and solutions.

The ideal candidate will have strong expertise in data architecture, cloud data platforms, data engineering, ETL/ELT, data modelling, and modern analytics ecosystems. This role requires a hands-on technical leader who can work closely with business stakeholders, architects, data scientists, and engineering teams to build reliable and high-performance data solutions.

Key Responsibilities

• Lead the architecture and design of enterprise-scale data platforms and data pipelines.
• Design scalable data lakes, data warehouses, lakehouses, and modern data architectures.
• Define data architecture standards, patterns, frameworks, and best practices.
• Develop and optimize ETL/ELT pipelines for structured and unstructured data.
• Design efficient data models, schemas, dimensional models, and data structures.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Build highly scalable batch and real-time/streaming data processing solutions.
• Lead technical discussions and provide architectural guidance to Data Engineers and Developers.
• Collaborate with business stakeholders to translate requirements into technical data solutions.
• Ensure data quality, governance, security, lineage, and compliance.
• Optimize data pipelines and platforms for performance, scalability, reliability, and cost.
• Establish CI/CD and DevOps practices for data engineering and deployment.
• Mentor and guide junior and senior data engineers.
• Conduct technical reviews and ensure adherence to architecture and coding standards.
• Evaluate new technologies and recommend appropriate tools and platforms.

Required Technical Skills

• Strong experience with Python and/or Scala
• Advanced SQL
• Batch and real-time data processing
• Data Lake / Data Warehouse / Lakehouse
• BigQuery / Redshift / Synapse
• Kafka / Kinesis / Event Hubs
• Distributed data processing
• Real-time streaming architectures
• Star and Snowflake schemas
• Data Vault
• Logical and physical data modelling
• Master Data Management
• Data governance and data lineage

DevOps & Infrastructure

• Docker
• Terraform
• Git
• Infrastructure as Code

Preferred Skills

• Experience with Databricks and Delta Lake
• Strong knowledge of Snowflake
• Experience with Data Mesh / Data Fabric architectures
• Knowledge of MLOps and AI/ML data platforms
• Experience with APIs and microservices
• Knowledge of data security and privacy frameworks
• Experience working in large enterprise environments

Leadership Responsibilities

• Own the technical architecture for critical data initiatives.
• Provide technical leadership across multiple data engineering teams.
• Review architecture, code, and technical designs.
• Define engineering standards and best practices.
• Identify technical risks and provide mitigation strategies.
• Mentor engineers and support their technical growth.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.