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Formula.Monks

Data Platform Engineer

Posted 9 Days Ago
Be an Early Applicant
Remote
12 Locations
Mid level
Remote
12 Locations
Mid level
Build and maintain data platforms using cloud infrastructure and tools, develop ETL pipelines, support data science frameworks, and manage production services.
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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)

Top Skills

AWS
C++
GCP
Go
Java
Jupyter
Kafka
Kubeflow
Kubernetes
Linux
Mlflow
MySQL
Pandas
Postgres
Presto
Python
PyTorch
Redshift
Rust
Scikit-Learn
Snowflake
SQL

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