Senior Python Data Engineer — DataOps & ELT Architect

Proxify AB; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

On-time monthly payments

Flexible withdrawal options

Flex days

Job summary

Proxify AB is seeking a Senior Data Engineer to architect and scale data foundations for a high-growth client product. The ideal candidate is a Python expert who treats data infrastructure as software, implementing CI/CD, unit testing, and observability across the modern data stack.

Responsibilities include building scalable ELT/ETL pipelines, testing, and cost optimization, collaborating with Data Scientists and Product Managers to translate business needs into robust data models.

Qualifications

• 5+ years building complex data processing using Python (Pandas/PySpark/Dask).
• Advanced SQL for transformations and optimization in cloud warehouses.
• Proficient with dbt for ELT, including docs and tests.
• Experience with Airflow/Prefect/Ddagster for dependencies.
• Hands-on with Snowflake/BigQuery/AWS Redshift and data modeling.
• Git, Docker, and CI/CD for data pipelines.

Responsibilities

• Build and maintain scalable ELT/ETL pipelines as a single source of truth.
• Implement automated tests and monitoring for data integrity.
• Optimize warehouse storage and compute costs; reduce latency.
• Collaborate with Data Scientists and Product Managers on data models.
• Promote DataOps culture via code reviews and best practices.

Skills

Python

SQL

dbt

Airflow

Cloud Data Warehouses

Dimensional Modeling

Git/Docker/CI‑CD

Tools

Terraform

Job description

Proxify AB is seeking a Senior Data Engineer to architect and scale data foundations for a high-growth client product. The ideal candidate is a Python expert who treats data infrastructure as software, implementing CI/CD, unit testing, and observability across the modern data stack.

Responsibilities include building scalable ELT/ETL pipelines, testing, and cost optimization, collaborating with Data Scientists and Product Managers to translate business needs into robust data models.