Senior Data Engineer

As a Senior Data Engineer at LoyaltyLion, your primary responsibilities include designing, implementing, and maintaining a state-of-the-art Data Lake and Data Warehouse. You will work closely with the product and infrastructure teams to create data models and tooling, ensuring that merchants can effectively explore and visualize their data. You will also write clean, scalable code in an Agile environment and engage in peer reviews to maintain the highest quality standards.

To apply for the Senior Data Engineer role at LoyaltyLion, you should have a minimum of 3 years of experience working with Python or Scala, along with substantial experience in designing and implementing data platforms. Familiarity with tools such as dbt, Superset, and Apache Airflow is essential. Ideal candidates should also have a solid understanding of data quality processes and experience in eCommerce.

At LoyaltyLion, professional growth is a priority. As a Senior Data Engineer, you will have the opportunity to work closely with our Data Lead, focusing on your personal development. We offer competitive learning and development budgets, providing resources for you to continuously enhance your skills and stay ahead in the ever-evolving data landscape.

As a Senior Data Engineer at LoyaltyLion, you will engage with a diverse data stack which includes Python, SQL, dbt, Apache Airflow, Docker, and Rabbit MQ, among others. You’ll also have exposure to advanced data tooling and platforms like ClickHouse, Superset, and a variety of AWS technologies, ensuring that you will be well-equipped to handle the challenges presented by our data-driven environment.

Yes, the Senior Data Engineer position at LoyaltyLion is fully remote! We promote flexible working arrangements, allowing our tech team to thrive from the comfort of their homes or choose to work from our office in Farringdon. Additionally, we offer international remote working options for up to 30 days a year, making it easier for you to explore the world while contributing to our exciting projects.

When answering this question, focus on specific projects or tasks where you've utilized Python in your data engineering work. Highlight your understanding of libraries like Pandas or NumPy for data manipulation, or frameworks like Apache Airflow for orchestration. Emphasize how Python has helped you build effective data pipelines or analytics tools.

In your response, clearly differentiate between a data lake and a data warehouse. Explain that a data lake is designed to store unstructured and raw data from various sources, allowing for easy data ingestion, whereas a data warehouse is structured for analysis and reporting, often containing processed data. Share any personal experience with implementing either technology.

Discuss strategies you’ve implemented to enhance performance, such as indexing databases or optimizing queries, and ensuring reliability through rigorous testing practices and monitoring tools. Providing specific examples from past experiences will demonstrate your hands-on expertise.

Share your experience working with tools like Superset or Tableau for data visualization. Discuss how these tools help stakeholders visualize complex data, derive insights, and make informed decisions. Mention any specific instances where your visualizations led to successful outcomes.

When addressing this question, pick a specific data challenge you faced—such as data inconsistency or slow processing. Describe your method for problem-solving, including any collaborative efforts with teammates, and the outcome of your solution to highlight your analytical and collaborative skills.

Explain your understanding of Agile principles and share specific experiences where you've worked within an Agile SCRUM team. Discuss how you’ve contributed to sprints, scrum meetings, and the iterative development process to lead projects toward success.

Talk about your familiarity with dbt and how you’ve used it to create reliable data models. Discuss the advantages of using dbt in your workflow, such as version control or collaborative model development, to showcase your technical proficiency.

When answering this question, emphasize the importance of peer reviews in maintaining quality and fostering collaboration. Discuss your approach to providing constructive feedback, and how you incorporate others' suggestions into your work to achieve the best possible results.

Discuss the critical role of data quality in ensuring reliable outputs and decisions based on data. Share specific strategies you employ, such as implementing validation checks, maintaining data lineage, or using automated testing frameworks to uphold data integrity.

Your answer should reflect an understanding of LoyaltyLion's mission to enhance customer engagement, as well as enthusiasm about collaborating with a talented team in a remote-first environment. Discuss how your skills and values align with LoyaltyLion’s goals, especially in the booming eCommerce landscape.