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 https://www.linkedin.com/company/tekever/