SENIOR DATA ENGINEER

SENIOR DATA ENGINEER (H/F)

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STATERA is an engineering and consulting company specialized in delivering IT and Digital transformation projects for major international organizations.

We support our clients on complex and business-critical initiatives across Data, Cloud, DevOps, Cybersecurity, Software Engineering, AI and Digital Transformation.

Our approach is built around flexibility, adaptability and long-term partnerships, enabling our consultants to work on high-impact projects within demanding technical environments.

As part of our growth, we are currently looking for a Senior Data Engineer to join one of our international clients and contribute to the design and implementation of modern, scalable data platforms.

Permanent Contract (CDI)

Location: Remote (European time zones only)

Occasional onsite travel may be required for workshops, project kick-offs or strategic alignment meetings.

Start date: ASAP

CONTEXT

You will join an international Data Engineering team responsible for delivering enterprise-grade data platforms, analytics capabilities and business-oriented data products across multiple European entities.

Working alongside Product Owners, Business Analysts and business stakeholders, you will design scalable data solutions capable of supporting operational reporting, KPI monitoring and strategic decision-making.

The environment combines strong engineering standards with a pragmatic delivery approach, requiring solutions that are scalable, maintainable and aligned with modern cloud data architectures.

MAIN RESPONSIBILITIES

Data Platform & Architecture

• Design scalable end-to-end data architectures.
• Build multi-layer data platforms (Raw / Curated / Consumption).
• Ensure consistency with enterprise data architecture standards.

Data Engineering

• Design, develop and optimise ETL / ELT pipelines.
• Build reusable transformation models.
• Deliver production-ready data pipelines.

Data Modelling

• Design dimensional data models (Star Schema).
• Create certified datasets and reporting-ready data marts.
• Standardise KPI-oriented datasets.

Data Quality & Governance

• Ensure data integrity, quality and consistency.
• Apply governance standards and access control policies (RBAC).
• Implement monitoring and validation processes.

Performance & Optimisation

• Optimise Snowflake workloads and SQL queries.
• Improve pipeline performance and cloud cost efficiency.
• Participate in continuous platform optimisation.

Collaboration

• Work closely with Product Owners, Business Analysts and technical teams.
• Support Agile delivery and contribute to engineering best practices.
• Participate in technical documentation and knowledge sharing.

PROFILE REQUIRED

Experience

• 8+ years of experience as a Data Engineer.
• Proven experience delivering enterprise-scale data platforms.
• Experience working within complex international environments.

Technical Skills

• Advanced SQL.
• Strong data modelling expertise.
• ETL / ELT design.
• Apache Airflow.
• dbt.
• Snowflake.
• AWS (or equivalent cloud platform).
• Git.
• CI/CD.
• Agile / Scrum.

Nice to Have

• Data Governance.
• RBAC.
• Data Lifecycle Management.
• Performance optimisation.
• Monitoring & Observability.

Soft Skills

• Strong analytical mindset.
• Pragmatic problem-solving approach.
• Ability to communicate with both business and technical stakeholders.
• Autonomous and delivery-oriented.
• Comfortable working within distributed international teams.

TECHNICAL ENVIRONMENT

• Snowflake
• AWS
• dbt
• Apache Airflow
• SQL
• Git
• CI/CD
• Jira
• Confluence
• Lucid

LANGUAGE REQUIREMENT

Fluent English (spoken and written) is mandatory. xuezdbg

All meetings, documentation and day-to-day communication are conducted entirely in English.

WHAT YOU WILL DELIVER

• Production-ready ETL / ELT pipelines
• Enterprise-grade Snowflake data models
• Scalable orchestration workflows (Airflow)
• dbt transformation models
• Data quality and monitoring frameworks
• KPI-ready datasets
• Technical documentation and knowledge transfer
• Continuous optimisation recommendations for data platforms