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Data Platform Engineer

Join us at Gorilla and be part of a mission to transform the energy industry. At Gorilla you'll play a vital role in developing cutting-edge data solutions that drive us towards a net-zero future. Our focus is on crafting efficient, reliable, and flexible software applications to tackle the unique challenges of data processing and analysis in the energy sector. Together, we're not only driving digital transformation and maximizing ROI for our clients but also contributing to the global effort of achieving net-zero emissions through technology and data-driven insights

Your Role

You will play a hands-on role in developing Gorilla’s data infrastructure. As a Data Engineer, you will design and maintain large-scale data pipelines, implement high-quality engineering practices, and enable efficient data processing to support our SaaS products. You'll bring a strong software engineering mindset to data systems, ensuring they are robust, scalable, and aligned with business goals.

You will also work cross-functionally with product, engineering, and operations teams, contributing to the evolution of our data systems while fostering a culture of collaboration, innovation, and accountability.

  • Build large-scale data pipelines: Design and optimize ETL pipelines and streaming solutions capable of processing terabytes of data efficiently, leveraging Python and tools like Airflow and DBT.

  • Enhance data infrastructure: Develop and maintain data systems in cloud environments (e.g., AWS, Azure, or GCP), utilizing infrastructure-as-code tools such as Terraform and Docker.

  • Collaborate across teams: Work closely with engineering, product, and business stakeholders to understand data needs, align architecture with business goals, and deliver impactful solutions.

  • Streamline workflows: Implement and manage workflow tools to automate and optimize data dependencies and ensure reliable data delivery.

  • Improve scalability and performance: Design systems that meet the growing demands of our platform, ensuring high availability, low latency, and scalability.

  • Reduce technical debt: Modernize existing infrastructure and improve maintainability through best practices in software engineering and DevOps.

  • Champion documentation: Create clear, comprehensive documentation for systems, processes, and solutions to promote knowledge sharing and alignment.

What You'll Need

  • Proven experience in data engineering: Expertise in designing and building robust data pipelines for large-scale processing, with a focus on efficiency and maintainability.

  • Cloud expertise: Strong experience deploying data solutions in cloud environments using tools like Terraform, Docker, and Kubernetes.

  • Software engineering mindset: Proficiency in Python with a solid foundation in OOP principles; familiarity with JVM and Scala systems is a plus.

  • Workflow management: Experience with tools like Airflow and DBT to automate and manage data processes effectively.

  • DevOps knowledge: Hands-on experience with CI/CD pipelines, infrastructure-as-code practices, and automation.

  • Strong collaboration skills: Ability to work cross-functionally, gather requirements, and translate business needs into technical solutions.

  • Problem-solving mindset: Analytical approach to tackling challenges, with a focus on continuous improvement and innovation.

About the Product Team

Moving from a startup to a scale-up we are keeping our innovative spirit whilst we build the foundations of tomorrow's energy retailers software and data infrastructure. Product is the foundation of our company and needs to perform at a top level to make our vision a success. Product is driven by many talented and opinionated people who are eager to drive our vision forward. It is the place where engineering, technology, data, architecture and energy expertise come together to make a difference.

Where and How You'd Work

As engineering team lead you are expected to be present and guide the team which is mostly based in our Antwerp office. This can be done partially remotely but we do expect you to bring the team together on key moments and make sure they are motivated and empowered.

Office Mix

This role is currently an Office-Mix Hybrid role. This means you would chat with your leader and team to define the number of days you need to be together to collaborate and achieve outcomes in close proximity. This is often 1 - 2 days a week. The other days you have flexibility.

This opportunity is for you if

  • You want to inspire and teach team members, the company and customers on the benefits of a strong data strategy.

  • You love talking to customers and stakeholders about data and data ecosystems both high level and more low level.

  • You get excited from pushing and organising the team to create incredible steps forward and realise our vision and want to motivate and guide them each step of the way.

What's in it for you

  • Flexible work options - whether you choose Office Mix or Remote First Mix (currently available within certain timezones and locations). We offer country-specific mobility benefits, and the ability to work flexible hours. You will be equipped with the best technology for remote work.

  • A job with purpose At Gorilla, we’re not just watching the world change—we’re making it happen! We provide cutting-edge data services to energy retailers, helping them tackle climate change while keeping the lights on; we’re here to make a big impact and have some fun along the way.

  • Renumeration Approach which is clear and no-nonsense based on your experience and location.

  • Core Benefits - Wherever your location, you can expect a generous PTO allowance and health insurance coverage.

  • Career Growth opportunities As Gorilla is growing at an incredible pace, you can leave your mark – growing alongside Gorilla. Lifelong learning is part of our DNA, and we care about your individual dreams and ambitions, beyond just work.

  • International Travel We host Gorilla Company Wide Gatherings where we all get a chance to see each other in real life. Past locations have included Portugal, Amsterdam, and Wallonia.

What You Should Know About Data Platform Engineer, Gorilla

Join the innovative team at Gorilla in Antwerp as a Data Platform Engineer, where your role will be pivotal in transforming the energy industry. At Gorilla, we're on a mission to build cutting-edge data solutions that contribute to a net-zero future. As a Data Platform Engineer, you’ll have the opportunity to develop robust data architectures and drive the creation of efficient and scalable software applications tailored to the unique challenges in data processing and analysis for the energy sector. You’ll be hands-on in designing, maintaining, and optimizing large-scale data pipelines and systems while collaborating with cross-functional teams to ensure our data infrastructure aligns with business goals. If you're passionate about leveraging technology to tackle climate change, this role is perfect for you! You'll work with advanced tools and frameworks, such as Python, Airflow, and cloud services like AWS and Azure, to streamline workflows. Here at Gorilla, we foster a culture of innovation and accountability, ensuring that you’re supported every step of the way. With our unique combination of a startup spirit and scale-up ambition, your contributions will have a direct impact on our mission while you enjoy flexible work options and abundant growth opportunities. Let's revolutionize the energy sector together at Gorilla!

Frequently Asked Questions (FAQs) for Data Platform Engineer Role at Gorilla
What are the key responsibilities of a Data Platform Engineer at Gorilla?

As a Data Platform Engineer at Gorilla, your key responsibilities include designing and maintaining large-scale data pipelines, enhancing our data infrastructure using cloud technologies, and collaborating with various teams to identify data needs. You'll also implement high-quality engineering practices to ensure efficient data processing and support our SaaS products, while eliminating technical debt through modernization efforts.

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What qualifications are necessary for the Data Platform Engineer position at Gorilla?

To be successful in the Data Platform Engineer role at Gorilla, you should have proven experience in data engineering, showcasing expertise in pipeline design and cloud deployment. Proficiency in Python and familiarity with tools like Airflow and DBT are essential. A solid understanding of DevOps practices, infrastructure-as-code, and strong collaboration and problem-solving skills are also key qualifications.

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How does the Data Platform Engineer at Gorilla contribute to environmental goals?

The Data Platform Engineer at Gorilla plays a critical role in supporting our mission to combat climate change by developing data-driven solutions that help energy retailers optimize their operations. Through the design and implementation of efficient data systems, you'll enable clients to make informed decisions that support net-zero emission targets, thereby directly contributing to our environmental goals.

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What tools and technologies should a Data Platform Engineer at Gorilla be familiar with?

Candidates for the Data Platform Engineer position at Gorilla should be proficient in using tools such as Python, Airflow, DBT for data pipeline management, and have experience with cloud platforms like AWS, Azure, or GCP. Knowledge of infrastructure-as-code with Terraform, container tools like Docker, and CI/CD pipelines are also highly beneficial.

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What type of work environment can a Data Platform Engineer expect at Gorilla?

At Gorilla, Data Platform Engineers can look forward to a flexible work environment with hybrid options that promote collaboration and team engagement. While there’s the flexibility of remote work, team members are encouraged to come together in our Antwerp office on key occasions to foster motivation and camaraderie.

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Common Interview Questions for Data Platform Engineer
Can you describe your experience with designing data pipelines as a Data Platform Engineer?

When discussing your experience designing data pipelines, focus on specific projects where you architected ETL processes, the tools you used like Airflow or DBT, and any challenges you overcame. Highlight your approach to ensuring scalability, efficiency, and maintenance in your designs to demonstrate your expertise.

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What cloud technologies have you worked with in your previous Data Engineering roles?

In your answer, cite specific cloud platforms such as AWS, Azure, or GCP, and describe the projects where you implemented data solutions. Be sure to mention any infrastructure-as-code tools like Terraform and how these experiences contribute to your qualifications for the Data Platform Engineer role at Gorilla.

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How do you ensure data quality while managing large-scale data pipelines?

Discuss the methodologies you use to maintain data quality, such as implementing monitoring tools, conducting regular audits, and using validation checks in your pipelines. Providing examples of your proactive measures for quality assurance will illustrate your thorough understanding of the importance of data integrity.

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What strategies have you used to collaborate effectively with cross-functional teams?

Share examples of how you’ve collaborated with product, engineering, or operations teams to gather requirements and translate them into technical solutions. Emphasize the importance of communication and aligning your technical work with business objectives to showcase your collaborative skill set.

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Describe a challenging problem you've solved as a Data Engineer.

Be prepared to explain a specific challenge you faced, the steps you took to analyze the problem, your thought process in developing a solution, and the outcome. Providing measurable results can significantly strengthen your response.

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How do you prioritize tasks when managing multiple data projects?

Explain your approach to prioritization, such as assessing project deadlines, the impact on the business, and resource availability. Highlight how effective communication with stakeholders helps you manage expectations and adjust priorities as necessary.

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What practices do you follow for documentation in your data engineering projects?

Discuss your commitment to thorough documentation, including how you maintain clear records of your architecture, data flows, and processes. Providing examples of documentation tools you utilize will help demonstrate your thoughtful approach to knowledge sharing.

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How do you keep up with new technologies in Data Engineering?

Tell the interviewer about the resources you utilize to stay current with the latest trends and technologies, such as attending webinars, following industry blogs, or participating in online courses. This shows your commitment to continuous learning as a Data Platform Engineer.

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What role does automation play in your data engineering work?

Explain how you’ve implemented automation in tasks like data ingestion, processing, and reporting. Highlight how automation increases efficiency, reduces errors, and frees up time for more complex analysis or development work.

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Can you give examples of how you have reduced technical debt in your data systems?

Share specific initiatives you’ve led or participated in to modernize data infrastructure, such as refactoring code, updating legacy systems, or employing best practices in DevOps to improve maintainability and scalability.

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DATE POSTED
December 18, 2024

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