Analytics Engineer - Data Modeling Engineeer - Remote (LATAM)

FlowMo·Remote(Colombia)
Data & Analytics

WFA Digital Insight

The demand for skilled analytics engineers has been on the rise, with a 25% increase in job postings over the past year. As companies seek to turn their data into actionable insights, professionals with expertise in data modeling and SQL are in high demand. FlowMo, a leader in AI systems, is looking for an Analytics Engineer to join their team. With the ability to work remotely and a focus on independence and speed, this role is ideal for those who thrive in fast-paced environments. Before applying, candidates should be aware that they will be working with real customer data from day one and will need to operate with minimal structure and high accountability.

Job Description

About the Role

The Analytics Engineer role at FlowMo is a unique opportunity for a skilled data professional to join a fast-paced and dynamic team. As an Analytics Engineer, you will be responsible for developing and maintaining complex data models using SQL and DBT. You will work closely with the founders and core product team to answer key business questions and drive growth.

The role entails working with messy and incomplete data to produce actionable insights quickly. You will need to be comfortable working in a remote environment with minimal structure and bureaucracy. The company values independence, speed, and ownership, and you will be expected to operate with high accountability and minimal supervision.

FlowMo is a small, fast-moving team that is passionate about turning business data into real results. The company is looking for someone who can think critically, work independently, and communicate complex ideas effectively.

What You Will Do

  • Develop and maintain complex data models using SQL and DBT
  • Answer key business questions such as CAC, LTV, attribution, and revenue drivers
  • Debug and fix broken or incomplete datasets
  • Translate business questions into structured data models
  • Iterate quickly and improve outputs over time
  • Ship usable results fast, not perfect results slowly
  • Work with real customer data from day one
  • Operate with minimal structure and high accountability
  • Collaborate with the founders and core product team to drive growth

What We Are Looking For

  • 2-5+ years of experience working in data modeling in a business context
  • Experience with data modeling tools such as DBT, LookML, or similar
  • Strong written and spoken English skills
  • Ability to work overlapping U.S. hours (EST)
  • Comfortable working with messy or incomplete data
  • Strong problem-solving skills and attention to detail
  • Ability to work independently with minimal supervision
  • Experience working in a fast-paced environment with minimal bureaucracy

Nice to Have

  • Experience working with AI systems and machine learning models
  • Knowledge of data visualization tools such as Tableau or Power BI
  • Experience working in a remote team environment
  • Familiarity with Agile development methodologies

Benefits and Perks

  • Fast-paced environment with minimal process and bureaucracy
  • Opportunity to grow into a customer-facing analytics or solutions role
  • Work directly with founders and core product team
  • Flexible, remote-first work environment
  • Opportunity to work with real customer data from day one
  • High degree of autonomy and ownership
  • Access to cutting-edge tools and technologies
  • Competitive compensation and benefits package

How to Stand Out

  • Make sure you have a strong portfolio that showcases your data modeling skills and experience working with SQL and DBT.
  • Be prepared to answer technical questions about your experience working with data modeling tools and your approach to debugging and fixing broken datasets.
  • Highlight your ability to work independently and with minimal supervision, as well as your experience working in fast-paced environments with minimal bureaucracy.
  • Show a willingness to learn and adapt to new tools and technologies, and be prepared to discuss your experience working with AI systems and machine learning models.
  • Don't be afraid to ask questions during the interview process, and be prepared to provide specific examples of your experience working with real customer data.
  • Be prepared to discuss your salary expectations and negotiation strategy, and make sure you have a clear understanding of the company's benefits and perks package.
  • Research the company culture and values, and be prepared to discuss how you align with their mission and vision.

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