Remote Data Engineer — Data Platform & Pipelines

Reppls (Techstars '24); Poland; On-site; PLN 263,000 - 314,000; Full time

Benefits offered by this job

Remote work from Eastern Europe / LatA

Job summary

Reppls (Techstars '24) is seeking an experienced Data Engineer to own and grow the data pipeline and platform infrastructure for quantitative investing workflows. You will work closely with data scientists, engineers, and portfolio managers to ensure clean, well-aligned data across research, reporting, and live trading environments.

You will leverage Python, Snowflake, Airflow, and dbt on AWS (S3/Athena) with infrastructure-as-code tooling (Terraform/CloudFormation/Pulumi).

Qualifications

• 5+ years of professional, hands-on data engineering experience.
• Strong understanding of data warehouse principles.
• Production experience with Python, Snowflake, Airflow, and DBT.
• Hands-on experience with AWS, especially S3 and Athena.
• Infrastructure as Code experience: Terraform, CloudFormation, Pulumi, or equivalent.
• Familiarity with Git, PRs, code reviews, tests, and CI.
• Extreme attention to detail and data quality from a business perspective.
• Excellent verbal and written English.

Responsibilities

• Own, operate, and improve the data pipeline across sources and environments.
• Incorporate new data sources with proper time-series alignment and leakage prevention.
• Set up and manage the reporting pipeline behind P&L, returns, and risk reporting.
• Manage the cloud infrastructure of the data platform as code.
• Provide development and operational support to data science and trading infra teams.
• Align data products with high-level business objectives and priorities.

Skills

Data engineering

Data warehousing

Python

Snowflake

Airflow

dbt

AWS

S3

Athena

IaC

Terraform

CloudFormation

Pulumi

Git

Code reviews

Testing

English

Tools

Snowflake

Airflow

dbt

AWS

S3

Athena

Terraform

CloudFormation

Pulumi

Git

Job description

Reppls (Techstars '24) is seeking an experienced Data Engineer to own and grow the data pipeline and platform infrastructure for quantitative investing workflows. You will work closely with data scientists, engineers, and portfolio managers to ensure clean, well-aligned data across research, reporting, and live trading environments.

You will leverage Python, Snowflake, Airflow, and dbt on AWS (S3/Athena) with infrastructure-as-code tooling (Terraform/CloudFormation/Pulumi).