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Analytics Engineer

Flex is building a finance super app for business owners — reimagining every single aspect of the financial workflow and financial services for any entrepreneur. The company has grown revenue 25x+ since publicly launching in September 2023 and is on track to achieve profitability by early 2025. Flex is focused on mid-market businesses ($3 - $100M revenue) that are largely overlooked by existing fintech solutions and reliant on slow and outdated regional banks.  We are targeting a ~$1T revenue opportunity that is largely up for grabs.


Flex is a fully remote company and this role can be performed from anywhere.


The Role


We are looking for engineers who are excited to be part of our early story and help us build a diverse and vibrant company. As a analytics engineer you will focus on building robust models, ensuring consistency across the models we build for the business, and creating documentation that enables downstream teams to access, understand, and use data effectively. You should have a strong sense of ownership and enjoy taking projects from inception to release. As an early employee, you’ll be working with a nimble team of committed and talented engineers and having a large, long-term impact on technical design and engineering culture.


What You’ll Do
  • Develop and maintain core data models in dbt to support key business metrics and ensure data consistency.
  • Collaborate across departments to define business metrics and ensure proper data infrastructure to serve them.
  • Ensure downstream teams can access and utilize data effectively by providing comprehensive documentation and support.
  • Collaborate with other engineers to ensure we’re providing consistent data across the entire organization.
  • Drive data quality initiatives by building monitoring systems and creating processes that guarantee accurate, auditable data.
  • Regularly audit and review data models to maintain their relevance and accuracy, ensuring long-term data integrity across the organization.


What You Need
  • You have 5+ years of working experience working with data, with a focus on data pipeline tools
  • You are an expert with SQL and have deep experience working with modern data transformation tools, such as dbt or similar, to create and manage scalable data models.
  • You have experience building and maintaining data pipelines in cloud-based environments such as Snowflake, Redshift, or BigQuery, ensuring data is easily accessible and reliable.
  • You enjoy digging into data discrepancies or issues to determine and fix root causes, ensuring high standards of data integrity across the organization.
  • You have hands-on experience with data visualization tools (e.g., Looker, Tableau, Power BI) to build or support self-serve dashboards that empower non-technical teams.
  • You have an interest in data quality, including the ability to design systems that ensure accuracy and consistency of key business metrics.
  • You focus on impact, finding the things you can deliver that deliver the most value for stakeholders.
  • You have exceptional communication skills, and are comfortable working independently with executive level team members
  • You are humble, highly motivated, and thrive in fast-paced environments
  • You have a proven ability to proactively manage your own priorities and dependencies in alignment with cross-functional dependencies and product/business impact.


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Average salary estimate

$115000 / YEARLY (est.)
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What You Should Know About Analytics Engineer, Flex

Flex is on the lookout for an innovative Analytics Engineer to join our dynamic team remotely. As part of a company that's redefining financial services for mid-market businesses, you'll be pivotal in shaping the future of our finance super app. Imagine working where you can truly make a difference and having a hand in developing data models that support key metrics for entrepreneurs who are often left behind by traditional banking solutions. Your main role as an Analytics Engineer will be to craft and maintain robust data models using dbt, championing data consistency across our organization. You will collaborate with various teams to define business metrics and set up a strong data infrastructure that ensures effective data access. Your documentation skills will empower downstream teams to utilize vital data in their workflows. We're excited to have someone who has a genuine passion for data quality and can innovate ways to monitor and maintain data integrity. With a thriving company culture and a committed team of talented engineers, you'll have the opportunity to take ownership of impactful projects and help drive Flex towards our ambitious goal of achieving profitability by early 2025. If you’re motivated, humble, and ready to dive into a fast-paced environment, we’d love to hear from you!

Frequently Asked Questions (FAQs) for Analytics Engineer Role at Flex
What are the main responsibilities of an Analytics Engineer at Flex?

As an Analytics Engineer at Flex, your primary responsibilities will include developing and maintaining core data models using dbt, collaborating with various departments to establish and track business metrics, and ensuring seamless data access for downstream teams through comprehensive documentation. You'll also drive initiatives to guarantee data quality and conduct regular audits of data models to maintain their relevance and accuracy.

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What qualifications do I need to apply for the Analytics Engineer position at Flex?

To apply for the Analytics Engineer role at Flex, you should have a minimum of 5 years of experience working with data, particularly with data pipeline tools. Expertise in SQL and experience with modern data transformation tools like dbt are crucial, along with a strong background in building and maintaining data pipelines in cloud environments such as Snowflake or BigQuery. Hands-on experience with data visualization tools and a strong focus on data quality will also be beneficial.

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What tools and technologies will I work with as an Analytics Engineer at Flex?

As an Analytics Engineer at Flex, you will work with a variety of tools and technologies, including dbt for data modeling, SQL for querying databases, and cloud-based environments like Snowflake or Redshift to build robust data pipelines. Familiarity with data visualization platforms such as Looker, Tableau, or Power BI will also be essential to create dashboards that help non-technical teams leverage data effectively.

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How does Flex support the ongoing learning and development of its Analytics Engineers?

Flex believes in fostering growth and development among its employees. As an Analytics Engineer, you'll have the opportunity to engage in continuous learning, whether that's through online courses, workshops, or collaborative projects with your colleagues. The company's remote-first approach also allows you to manage your time and learn at your own pace, focusing on areas that matter most to your career.

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What type of work culture can I expect as an Analytics Engineer at Flex?

At Flex, you can expect a bright and inclusive work culture that values innovation, diversity, and autonomy. As a remote company, we encourage our team members to take ownership of their projects while collaborating with a dedicated group of talented engineers. You'll be part of a vibrant team focused on making a significant impact in the fintech space.

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Common Interview Questions for Analytics Engineer
Can you describe your experience with SQL and how you've used it in your previous roles?

In your answer, highlight specific SQL queries or functions you’ve used to pull insights from datasets. Discuss how you have optimized queries for performance or manage data integrity in reporting.

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What strategies do you use to ensure data quality and integrity?

Talk about your approach to building monitoring systems, conducting audits of data models, and implementing validation rules that help maintain accuracy and consistency of data.

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How do you collaborate with cross-functional teams to align data metrics?

Share examples of how you've partnered with teams like marketing, finance, or product departments to define key metrics and ensure the data infrastructure supports their needs.

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Describe a challenging project you worked on involving data pipelines. What was your role?

Discuss a specific project where you faced challenges, detailing your role, the tools you used, and how you overcame obstacles to deliver results effectively.

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How do you approach documentation to support data accessibility?

Explain your process for documenting data models and workflows, emphasizing clarity, thoroughness, and how your documentation has enabled teams to use data effectively.

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What experience do you have with data visualization tools?

Talk about specific tools you've used and describe projects where you created dashboards or visualizations that guided decision-making for non-technical stakeholders.

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In your opinion, what makes a successful analytics engineer?

Focus on attributes like communication skills, a problem-solving mindset, adaptability, and a strong sense of ownership of projects as key components for success in this role.

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Tell us about a time you discovered a data discrepancy. How did you address it?

Detail the context of the situation, the steps you took to investigate the discrepancy, and the solution you implemented to resolve the issue and prevent future occurrences.

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How do you prioritize your work when managing multiple projects?

Discuss your approach to prioritization, mentioning techniques you use to align your tasks with business goals and communicate effectively with stakeholders about timelines.

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What interests you about working at Flex and this Analytics Engineer position?

Share your enthusiasm for Flex's mission, focus on mid-market businesses, and how you see your skills contributing to building a financial super app that makes a real impact.

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Full-time, remote
DATE POSTED
January 11, 2025

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