TEKEVER > Data Platform Engineering Lead

Data Platform Engineering Lead

Data Platform Engineering Lead

Sector

Data & AI

Location

Europe - Remote

Employment Type

Full-time

 

Data Platform Engineering Lead

Are you ready to revolutionise the world with TEKEVER? 🚀🌍

Join us, the European leader in unmanned technology, where cutting-edge advancements meet unparalleled innovation. We offer a unique surveillance-as-a-service solution that provides real-time intelligence, enhancing maritime safety and saving lives. TEKEVER is setting new standards in intelligence services, data and AI technologies.

Become part of a dynamic team transforming maritime surveillance and making a significant impact on global safety. 🌐

At TEKEVER, our mission is to provide limitless support through mission-oriented game-changers, delivering the right information at the right time to facilitate critical decisions.

If you’re passionate about technology and eager to shape the future, TEKEVER is the place for you! 👇🏻🎯

 

Job Overview:

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 <hyperlink to Sr. Data / Platform Architect Job Description>. For an overview of what our Data Engineers do on a day-to-day basis, please refer to <hyperlink to Data Engineer Job Description>.
  • 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: Bachelor’s or Master’s 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 make a difference;
  • 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/

If the above excites you, send us your application to jobs@tekever.com! 🚀👩‍💻

Data Platform Engineering Lead

Sector

Data & AI

Location

Europe - Remote

Employment Type

Full-time

 

Data Platform Engineering Lead

Are you ready to revolutionise the world with TEKEVER? 🚀🌍

Join us, the European leader in unmanned technology, where cutting-edge advancements meet unparalleled innovation. We offer a unique surveillance-as-a-service solution that provides real-time intelligence, enhancing maritime safety and saving lives. TEKEVER is setting new standards in intelligence services, data and AI technologies.

Become part of a dynamic team transforming maritime surveillance and making a significant impact on global safety. 🌐

At TEKEVER, our mission is to provide limitless support through mission-oriented game-changers, delivering the right information at the right time to facilitate critical decisions.

If you’re passionate about technology and eager to shape the future, TEKEVER is the place for you! 👇🏻🎯

 

Job Overview:

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 <hyperlink to Sr. Data / Platform Architect Job Description>. For an overview of what our Data Engineers do on a day-to-day basis, please refer to <hyperlink to Data Engineer Job Description>.
  • 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: Bachelor’s or Master’s 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 make a difference;
  • 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/

If the above excites you, send us your application to jobs@tekever.com! 🚀👩‍💻