Formula.Monks

Data Platform Engineer

Posted 2 Days Ago

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Hiring Remotely in Bogotá, Bogotá, D.C.

Remote

Mid level

Information Technology

The Role

The Data Platform Engineer at Formula.Monks will build and maintain data platforms utilizing cloud infrastructure and handle data management and processing. Responsibilities include developing ETL processes, aiding in machine learning framework design, and ensuring high data quality while managing production services.

Summary Generated by Built In

Formula.Monks, part of Media.Monks and S4 Capital, is a global consulting firm mastering AI-powered transformations for the Fortune 100. We combine long-term strategic thinking, deep enterprise experience, and a human-centered approach to help clients transform business processes and dominate their industries.

About the Role

As a Data Platform Engineer, you’ll build cutting-edge data platforms that ingest, manage, and process data from various businesses. This role supports a wide range of use cases, including customer-facing APIs and large-scale machine learning models.

Responsibilities

Build and operate data platforms using public cloud infrastructure (AWS, GCP), Kafka, databases, and containers
Develop data science platforms leveraging open-source software and cloud services
Design and run ETL tools and frameworks to onboard data, define schemas, create DAG processing pipelines, and monitor data quality
Aid in the development of machine learning frameworks and pipelines
Manage mission-critical production services
Perform other related duties as assigned

Qualifications & Skills

3+ years of relevant experience in a Data Platform Engineering role
Strong software engineering skills with Python; additional experience in C++, Java, Go, or Rust is a plus
Proven expertise in building ETL and stream processing tools with technologies like Kafka, Spark, Flink, or Airflow/Prefect
Proficient in SQL and databases/engines such as MySQL, PostgreSQL, Snowflake, Redshift, or Presto
Familiarity with data science tools (e.g., Jupyter, Pandas, Scikit-learn, PyTorch) and frameworks like MLFlow or Kubeflow
Hands-on experience with AWS/GCP services, Kubernetes, and Linux in production environments
Strong inclination toward automation and DevOps practices
Capable of managing increasing data volume, velocity, and variety
Agile, self-starter mindset with strong communication skills
Ability to navigate ambiguity and prioritize tasks effectively
Participation in on-call support beyond standard business hours
Strong english Skills (B2)