At a Glance
- Tasks: Design and optimise data architectures using Python and SQL for impactful digital solutions.
- Company: Join Flywheel, a leader in digital commerce with a global presence.
- Benefits: Enjoy competitive pay, flexible work, and great learning opportunities.
- Other info: Collaborative culture with a focus on inclusion and personal growth.
- Why this job: Lead innovative data projects that drive real change in the AdTech and MarTech sectors.
- Qualifications: 5+ years as a Data Engineer with expertise in Snowflake and data orchestration.
The predicted salary is between 60000 - 80000 € per year.
About Flywheel's suite of digital commerce solutions accelerate growth across all major digital marketplaces for the world's leading brands. We give clients access to near real‐time performance measurement and improve sales, share, and profit. With teams across the Americas, Europe and APAC, we offer a career with real impact, endless growth opportunities and the support you need to be the best you can be.
Opportunity: As we architect the next wave of data solutions in the AdTech and MarTech sectors, we're on the lookout for a Senior Data Engineer, an expert in data architecture and pipeline design. If you're a seasoned expert, eager to lead, innovate, and craft state‐of‐the‐art data solutions, we're keen to embark on this journey with you.
What you'll do:
- Develop, test, and maintain data architectures in Snowflake using Python, SQL, and modern data orchestration frameworks to deliver on business requirements.
- Uphold data quality standards, implementing tools and frameworks to detect and rectify data inconsistencies and inaccuracies.
- Optimize pipelines and data structures to ensure peak performance.
- Identify and resolve bottlenecks by refactoring code and/or modifying flows.
- Drive initiatives for new data collection while refining existing data sources.
- Ensuring the highest standards of data integrity, accuracy, and reliability.
- Troubleshoot existing ETL pipelines and work with partners to resolve them in a timely manner.
- Develop and update technical documentation.
- Manage conflicting priorities and multiple projects concurrently.
Who you are:
- 5+ years of intensive experience as a Data Engineer or in a similar role, with a demonstrable track record of leading large-scale projects.
- Familiarity with Airflow, Dagster or similar data orchestration frameworks.
- Strong understanding of RESTful APIs as well as experience working with both synchronous and asynchronous endpoints.
- Experience with Snowflake or Redshift with a strong understanding of SQL.
- Proficient in Python and Pandas.
- Experience working with JSON and XML.
- Strong understanding of cloud computing concepts and services (AWS preferably).
- Experience with Git or equivalent version control systems and CI/CD pipelines.
- Familiarity with dbt a plus.
- Highly analytical with strong problem‐solving skills: ability to apply solutions forward, not just completing the task at hand.
- Ability to investigate, analyze and solve problems as well as clearly communicate results.
- Strong attention to detail, well organized, and can prioritize tasks under pressure.
- Must be a team player but also can work independently.
- Experience working in an agile product development environment.
Working at Flywheel: We have office hubs across the globe where team members can go to feel productive, inspired, and connected to others – team members go into Hub Offices 3× a week. Competitive paid time off, including annual leave plus paid public holidays. Great learning and development opportunities. Benefits that help you live your best life. Parental leave and benefits. Volunteering opportunities.
If you're looking to connect with teammates on a topic of inclusion and identity, chances are there's an ERG for that. The hired candidate will be required to complete a background check.
Learn more about us here: Life at Flywheel.
The Interview Process: Every role starts the same: an introductory call with someone from our Talent Acquisition team, where we will look for company and values fit as well as your professional experience. Depending on the role, you may also have technical questions during this call. Afterwards, you can expect to meet several people from the team 1:1 and there might be further skill assessments in the form of a take‐home assignment, live coding exercise or pair programming, depending on the specific role. In your initial call, we will walk you through exactly what to expect the process to be.
Inclusive Workforce: Flywheel Commerce Network's goal is to create a culture where all individuals of all backgrounds feel comfortable in bringing their authentic selves to work. We want all people to feel included and empowered to contribute fully to our vision and goals. Flywheel Commerce Network is an Equal Opportunity Employer and participates in E‐Verify. All applicants will receive fair consideration for employment. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability or any other applicable legally protected characteristics in the location in which the candidate is applying.
Senior Data Engineer in London employer: Flywheel
At Flywheel, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. With competitive benefits, including generous paid time off and extensive learning opportunities, we empower our employees to thrive both personally and professionally. Our global office hubs provide a vibrant environment for teamwork and creativity, making Flywheel an ideal place for Senior Data Engineers looking to make a meaningful impact in the AdTech and MarTech sectors.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Flywheel on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the technical interview by brushing up on your Python and SQL skills. Practice coding challenges that focus on data architecture and pipeline design, as these are key for the Senior Data Engineer role.
✨Tip Number 3
Show off your problem-solving skills! During interviews, be ready to discuss how you've tackled data inconsistencies or optimised pipelines in past projects. Real examples will make you stand out.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Flywheel team.
We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with data architecture and pipeline design. We want to see how your skills align with what we're looking for in a Senior Data Engineer.
Showcase Your Projects:Include specific examples of large-scale projects you've led or contributed to. We love seeing real-world applications of your skills, especially if they involve Snowflake, Python, or data orchestration frameworks like Airflow.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your achievements and experiences shine through without unnecessary fluff.
Apply Through Our Website:Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Flywheel
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Snowflake, Python, and SQL. Brush up on your knowledge of data orchestration frameworks like Airflow or Dagster, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've identified and resolved data bottlenecks or inconsistencies. Highlight your analytical skills and how you approach troubleshooting ETL pipelines, as this will demonstrate your ability to think critically under pressure.
✨Communicate Clearly
During the interview, practice articulating your thought process clearly. Whether you're discussing technical concepts or your past experiences, being able to communicate effectively is key. Remember, they want to see how you can convey complex ideas simply.
✨Emphasise Team Collaboration
Since the role requires both teamwork and independent work, be ready to share examples of how you've successfully collaborated with others in an agile environment. Discuss how you manage conflicting priorities and contribute to team goals, as this will show you’re a good fit for their culture.
