Requirements

Expected technologies

AWS Glue

DBT

Spark

Metabase

DataDog

Great Expectations

Postgres

TimescaleDB

Python

Our requirements

• 4+ years of experience in data analysis or applied data science.
• Strong programming skills in R and Python (data processing, automation, and analytics).
• Good understanding of time-series structures, streaming data, and complex data models.
• Experience working with APIs and integrating data from multiple systems.
• Familiarity with machine learning workflows and model validation.
• Exposure to tools and platforms such as AWS Glue, DBT, Spark, Metabase, DataDog, Great Expectations, Postgres, or TimescaleDB.

Optional

• Knowledge of R for analysis or visualization.
• Experience in regulated or data-sensitive industries (e.g., healthcare, aviation, transportation).
• Previous collaboration with research or scientific teams.
• Basic familiarity with a typed language (e.g., Go).

Your responsibilities

• Create and maintain analytical workflows and data processes handling time-series and structured data.
• Monitor and improve data quality, accuracy, and completeness across multiple sources.
• Support data modeling, feature preparation, and result validation for analytical and predictive use cases.
• Write efficient Python scripts for data transformation, automation, and integration with external APIs.
• Collaborate with product, research, and engineering teams to design relevant KPIs and analysis frameworks.
• Contribute to improving the analytics environment with tools like DBT, Metabase, AWS Glue, or Spark.