Data Platform Engineering Lead

Mission:

The Data Platform Engineering Lead will be responsible for overseeing the design, implementation and maintenance of our Data & Analytics platform, pipelines and infrastructure. This role requires a combination of strong technical expertise, leadership abilities and a strategic mindset. The ideal candidate will have a proven track record in data architecture, data engineering, cloud and on-premise technologies, with experience in managing a deeply technical team and driving complex projects to completion. This role involves collaborating with cross-functional teams to ensure our data platform is robust, scalable, secure and aligned with the company's strategic objectives.

What will be your responsibilities:

• Leadership: Lead and mentor a team of data architects and data engineers, fostering a collaborative and high-performance culture. For an overview of what our Data Architects do on a day-to-day basis, please refer to . For an overview of what our Data Engineers do on a day-to-day basis, please refer to .

• Platform Development: Oversee the design, development and maintenance of scalable and robust data architectures and pipelines, ensuring efficient data processing, storage and retrieval, including data ingestion, storage, processing, management and analytics components.

• Architecture Design: Develop and maintain the architecture of the data platform, ensuring it meets the needs of various business units and supports future growth.

• Technology Strategy: Define the technology stack and architecture standards for the data platform, ensuring alignment with industry best practices and emerging trends.

• Data Integration: Develop strategies for integrating diverse data sources, ensuring seamless data flow and high data quality.

• Scalability and Performance: Design solutions that can scale with growing data volumes and ensure optimal performance across the data platform.

• Performance Optimization: Continuously monitor and optimize the performance of the data platform to handle large-scale data efficiently.

• Security and Compliance: Implement robust data security measures and ensure compliance with relevant regulations and industry standards.

• Collaboration: Work closely with data scientists, analysts, product managers and other stakeholders to understand data requirements and deliver effective solutions.

• Innovation: Stay up-to-date with the latest advancements in data technologies and drive continuous innovation within the data platform.

• Documentation: Maintain comprehensive documentation of data pipelines, ETL processes and architectural decisions.

Profile and requirements:

• Education: Bachelors or Masters degree in Computer Science, Engineering, Information Systems, or a related field.

• Experience: 7+ years of experience in data engineering or a similar role, with at least 3 years in a leadership position.

• Technical Expertise:

  • Strong experience with Data Platform reference architectures (e.g. Lambda architecture, Data Mesh).

  • Deep knowledge of big data technologies (e.g., Hadoop, Spark, Kafka) and data warehousing solutions (e.g., Redshift, Snowflake).

  • Extensive experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud. Google Cloud certification is preferred.

  • Experience with migration from on-premise to cloud and vice versa.

  • Good knowledge of relevant security frameworks & standards.

  • Proficiency in programming languages such as Python, Java, or Scala.

  • Strong understanding of database management systems (e.g., SQL, NoSQL, NewSQL). Experience with SQL and database management systems (e.g., MySQL, PostgreSQL, SQL Server).

  • Knowledge of data integration tools and frameworks (e.g., Apache Nifi, Talend, Informatica).

  • Familiarity with data modeling, data warehousing and data governance practices.

  • Experience with Iaac (e.g. Ansible, Terraform), data pipeline orchestration (e.g. Airflow), log exploration tools (e.g. Streamlit, Dash), data extraction (e.g. PostGIS, Kafka, Airflow, FastAPI), pandas, scikit-learn, Docker.

  • Solid knowledge of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc.

• Analytical Skills: Strong analytical and problem-solving skills with a focus on delivering scalable and efficient data solutions.

• Leadership: Proven leadership skills with experience in building and leading high-performing teams.

• Communication: Excellent verbal and written communication skills, with the ability to effectively collaborate with technical and non-technical stakeholders.

• Project Management: Strong project management skills with the ability to manage multiple projects and priorities simultaneously.

• Attention to Detail: High attention to detail and a commitment to ensuring data quality and accuracy.

• Adaptability: Ability to work in a fast-paced, dynamic environment and manage multiple priorities simultaneously.

What we have to offer you:

• An excellent work environment and an opportunity to create a real impact in the world;

• A truly high-tech, state-of-the-art engineering company with flat structure and no politics;

• Working with the very latest technologies in Data & AI, including Edge AI, Swarming - both within our software platforms and within our embedded on-board systems;

• Flexible work arrangements;

• Professional development opportunities;

• Collaborative and inclusive work environment;

• Salary compatible with the level of proven experience.

Do you want to know more about us ?

Visit our LinkedIn page at