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Senior Data Engineering Manager

2 meses atrás

Porto, Porto, Portugal Planet Tempo inteiro

About Us:

Planet is a technology company that's transforming payments by putting the customer experience first. We help our customers deliver a better experience for guests, shoppers, and consumers everywhere. Our market continues to evolve and expand, partnering with the world's most prestigious brands across Retail and Hospitality, and with a network of Financial Services partners worldwide.

Our Vision:

To meet consumer demands, payments must be simple, safe, and invisible. The only way to do this is to fully embed payments in the software that runs business. By combining software and payment technology, we're creating a world of connected commerce, that makes payments feel good.

Our Team:

We're growing organically, and with strong Private Equity investors, Advent International and Eurazeo, we've the financial capital and expertise to grow our capabilities and reach through acquisition.

The Role:

The Senior Data Engineering Manager will lead and oversee the data engineering function, ensuring the successful design, implementation, and optimisation of the organisation's data architecture. This individual will manage a team of data engineers (including those using Snowflake, dbt, and Fivetran) and collaborate closely with cross-functional teams, including analytics, data science, IT, and business stakeholders, to deliver scalable, high-performing, and secure data infrastructure.

Key Responsibilities:

  1. Lead, mentor, and manage a team of data engineers, providing guidance on best practices, career development, and performance management.
  2. Foster a culture of collaboration, continuous learning, and innovation within the data engineering team.
  3. Develop and execute a strategic roadmap for the data engineering function, aligning it with organisational objectives and long-term goals.
  4. Ensure the team's data engineering efforts support business objectives such as improved decision-making, innovation, and scalability.
  5. Serve as the main point of contact for senior leadership, providing regular updates on data engineering initiatives and performance.
  6. Collaborate with business leaders and other stakeholders to identify data requirements and priorities.
  7. Oversee the design and implementation of the data infrastructure, focusing on cloud-based platforms (e.g., Snowflake).
  8. Ensure the architecture supports robust data integration, transformation, and storage solutions, including the use of tools such as Fivetran and dbt.
  9. Continuously evaluate and optimise the organisation's data systems for performance, reliability, scalability, and cost efficiency.
  10. Drive the adoption of best practices in ETL/ELT processes, data modelling, and data security.
  11. Implement and maintain robust data governance frameworks, ensuring that the organisation's data assets are managed in a compliant, secure, and well-documented manner.
  12. Oversee the development of data quality processes and standards, ensuring high levels of data accuracy, integrity, and consistency across the organisation.
  13. Manage risks associated with data architecture and ensure compliance with relevant data privacy regulations (e.g., GDPR).
  14. Stay abreast of emerging trends and technologies in data engineering, cloud infrastructure, and analytics.
  15. Assess and recommend new tools and technologies that could drive further efficiencies and improvements to the data engineering function.
  16. Foster a culture of continuous improvement, driving initiatives that enhance data engineering workflows, reduce time to insight, and improve collaboration across teams.
  17. Manage the data engineering budget, including personnel costs, infrastructure investments, and software licensing.
  18. Ensure effective use of resources, balancing immediate needs with long-term strategy.
  19. Oversee relationships with external vendors, particularly those involved in cloud infrastructure, data integration (e.g., Fivetran), and data transformation (e.g., dbt).

Requirements:

Technical Expertise:

Extensive experience with cloud-based data warehousing solutions, particularly Snowflake.

Proven expertise in ETL/ELT tools, such as Fivetran, and data transformation tools, particularly dbt.

Strong understanding of modern data engineering principles, data modelling, and data architecture.

Proficiency in SQL and experience with programming languages like Python is preferred.

Leadership & Management:

Demonstrated experience leading and managing data engineering teams, with a focus on mentorship and talent development.

Ability to drive data strategy at a senior management level, collaborating effectively with cross-functional teams.

Data Governance & Compliance:

Strong knowledge of data governance practices, including data security, privacy, and compliance regulations (e.g., GDPR).

Analytical & Problem-Solving Skills:

Excellent analytical skills with the ability to solve complex technical problems and make data-driven decisions.

Experience in troubleshooting and optimising large-scale data systems for high performance.

Communication & Stakeholder Management:

Exceptional communication skills, with the ability to engage with and present to senior stakeholders.

Experience managing expectations, delivering results, and navigating competing business priorities.

Why Planet:

Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need.

Come and grow your career in the most exciting, fast-paced technology market, with a business that delivers feel-good connected commerce. We would love to hear from you – Apply now.