Senior Data Engineer | Python Data Pipelines & DataOps

Mosaec; Town of Sweden (NY); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

On-time payments

Flexible working hours

Up to 24 flex days off

Job summary

Proxify AB in Sweden is seeking a Senior Data Engineer to architect and scale data foundations for high-growth client products. You are a Python expert who treats data infrastructure as software, implementing CI/CD, testing, and observability across the data stack.

You will design and build automated ELT/ETL pipelines, optimize warehouse costs, and collaborate with data scientists and product managers. Remote roles offer flexible collaboration with international teams and a strong DataOps

Qualifications

• 5+ years building complex data processing apps in Python.
• Advanced SQL for transformations, windows, and warehouse optimization.
• Deep experience with dbt for ELT management, docs and tests.
• Proven experience with Airflow, Prefect, or Dagster for DAGs.
• Hands-on with Snowflake, BigQuery, or Redshift.
• Strong understanding of Dimensional Modeling and Data Vault 2.0.
• Experience with Git, Docker, and CI/CD for data pipelines.

Responsibilities

• Build and maintain scalable ELT/ETL pipelines providing a single source of truth.
• Implement rigorous automated testing and monitoring for data integrity.
• Optimize warehouse storage and compute costs while reducing latency.
• Collaborate with Data Scientists and Product Managers to translate requirements.
• Promote a DataOps culture with code reviews and best practices.

Skills

Python

SQL

Data modeling

CI/CD

DataOps

Tools

dbt

Airflow

Git

Docker

Terraform

Pandas/PySpark/Dask

Snowflake

BigQuery

Redshift

Dagster

Job description

Proxify AB in Sweden is seeking a Senior Data Engineer to architect and scale data foundations for high-growth client products. You are a Python expert who treats data infrastructure as software, implementing CI/CD, testing, and observability across the data stack.

You will design and build automated ELT/ETL pipelines, optimize warehouse costs, and collaborate with data scientists and product managers. Remote roles offer flexible collaboration with international teams and a strong DataOps