Remote Data Engineer: Build scalable data pipelines & APIs

CodiLime; Poland; Hybrid; PLN 184,000 - 312,000; Full time

Benefits offered by this job

Flexible hours

Remote or hybrid options

Training budget

Onboarding support

Collaborative culture

Job summary

CodiLime is seeking a Data Engineer to join a team building a large-scale data platform. You will design, code, test, and operate production Python systems that move and transform data at scale, targeting a unified enterprise dataset with 300M+ records sourced from 10+ systems.

The role combines data engineering and software engineering, focusing on pipelines, services, and data models, with strong emphasis on testing, typing, and CI/CD.

Qualifications

• Strong Python experience with typed code and testing.
• Experience building and operating ETL/ELT pipelines in production.
• Experience with Snowflake and dbt.
• Experience with Airflow or similar orchestration tools.
• Excellent written and spoken English (C1)

Responsibilities

• Design, build, and maintain batch and streaming data pipelines in Python (Airflow).
• Write reusable, well-typed Python libraries and internal packages.
• Create Python services and APIs (FastAPI) for data access.
• Develop SQL/dbt models for fast, reliable querying on Snowflake.
• Write unit/integration/data-contract tests and CI pipelines.
• Profile and optimize Python code for performance and cost.
• Deploy and operate code in cloud using containers and CI/CD.
• Ensure data security and access controls across pipelines.
• Document data processes and system architecture.
• Collaborate with Data Architecture Lead and cross-functional teams to deliver value.

Skills

Python

SQL

English

Tools

Kubernetes

Airflow

Pandas

Polars

PyArrow

DuckDB

PySpark

PostgreSQL

Redis

FastAPI

API Gateway

Pydantic

Job description

CodiLime is seeking a Data Engineer to join a team building a large-scale data platform. You will design, code, test, and operate production Python systems that move and transform data at scale, targeting a unified enterprise dataset with 300M+ records sourced from 10+ systems.

The role combines data engineering and software engineering, focusing on pipelines, services, and data models, with strong emphasis on testing, typing, and CI/CD.