Data Analytics Engineer

The responsibilities of a Data Analytics Engineer at dv01 include managing and scaling business logic within the data pipeline, which encapsulates knowledge from hundreds of datasets. You’ll collaborate directly with analysts and customers to understand data complexities and integrate new datasets, ensuring our data remains accurate and actionable. Additionally, working with state-of-the-art technology such as DBT and Apache Spark is a core part of your role.

To qualify for the Data Analytics Engineer position at dv01, candidates should have at least 3 years of professional experience in data engineering, with a strong command of languages such as Python and SQL. Familiarity with data pipelines and the ability to express business logic through code are essential, along with a passion for working with financial datasets to enhance lending transparency.

Data Analytics Engineers at dv01 utilize a range of advanced open-source technologies, including DBT for data transformation and Apache Spark for big data processing. The role also involves working on the Google Cloud Platform, specifically tools like BigQuery and Cloud Run, making this an excellent opportunity for engineers passionate about cutting-edge technologies and cloud-based solutions.

At dv01, the work environment is remote-first and designed to foster flexibility and innovation. Employees are encouraged to work from wherever they feel most productive, be it home, a café, or a co-working space. The company promotes a culture of trust and collaboration, allowing engineers to thrive while making impactful contributions to structured finance.

Data Analytics Engineers at dv01 enjoy a comprehensive benefits package that includes unlimited PTO for well-deserved time off, a generous learning and development fund to fuel continuous growth, health insurance covering medical, dental, and vision, and fitness incentives to support a healthy lifestyle. Additionally, there are excellent family bonding leave policies for new parents, ensuring employees can balance work and personal life effectively.

In your answer, detail specific projects where you've designed or optimized data pipelines, mentioning the technologies you used, any challenges you faced, and the results of your work. Highlight how your experience relates to the needs of dv01, especially in managing financial data.

Discuss your methods for transforming raw data into usable formats, including techniques you've employed to ensure data accuracy. Provide examples of tools like Python or SQL scripts you’ve developed for these purposes. Relate this to the types of datasets dv01 works with, like loans and financial instruments.

Emphasize your familiarity with cloud platforms, particularly Google Cloud if applicable. Share specific services you have used, like BigQuery and Cloud Run, and mention any relevant projects where cloud technology facilitated data storage or processing.

Explain your strategies for effective communication and collaboration, including regular check-ins, gathering requirements, and being attentive to unclear data needs. By demonstrating your team-oriented mentality, you can show how you would smoothly transition into dv01’s collaborative environment.

Share a relevant example, detailing the business logic captured in the model, how you structured the tables, and the technologies utilized. Explain how this experience aligns with dv01's focus on managing complex financial datasets.

Articulate your passion for bridging data engineering with finance. Share what excites you about analytics in financial decision-making and how you hope to contribute to dv01’s mission of enhancing transparency in the lending process.

Discuss your optimization techniques, such as code reviews, profiling, and testing for performance. Mention specific instances where you proactively improved performance, particularly in relation to data processing tasks that might be relevant to dv01.

Mention tools like Git for version control and collaboration platforms such as GitHub or GitLab. Describe your workflow for managing code changes, working collaboratively on code reviews, and ensuring integration without disruption to ongoing projects.

Highlight the resources you use to stay informed, such as industry blogs, webinars, and participating in tech communities. Mention any recent trends, especially those relevant to financial data analytics, and how you plan to incorporate these into your work at dv01.

Share your insights on how data analytics can evolve in the finance sector, including trends like automation, artificial intelligence, and real-time data analysis. Discuss how you envision contributing to these advancements at dv01.