Proxify

Senior Data Engineer (Python)

Proxify
Time zone: CET (+/- 3 hours)Posted Discovered via the company's careers siteMatch locked
Remotefull time5+ years expDevelopment

Why you match

Sign in to see your match score, the skills that line up, and what's missing.

Match locked

About us

Talent has no borders. Proxify's mission is to connect top developers around the world with the opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction. 🙂 Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 5000+ talented developers trust Proxify and its network to fulfill their dreams and objectives. Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.

The Role

We are looking for a Senior Data Engineer to architect and scale the data foundations for one of our high-growth client products. The ideal candidate is a Python expert who treats data infrastructure as software, implementing CI/CD, unit testing, and observability into every layer of the modern data stack. You are a perfect candidate if you are growth-oriented, you love what you do, and you enjoy working on new ideas to develop exciting products.

What we’re looking for

• 5+ years of experience building complex data processing applications using Python (Pandas, PySpark, or Dask).

• Advanced SQL skills for complex transformations, window functions, and query optimization in cloud warehouses.

• Deep experience with dbt (data build tool) for managing the T in ELT, including documentation and testing.

• Proven experience with Apache Airflow, Prefect, or Dagster for managing complex dependency graphs.

• Hands-on experience with Snowflake, BigQuery, or AWS Redshift.

• Strong understanding of Dimensional Modeling (Star/Snowflake schema) and Data Vault 2.0.

• Experience with Git, Docker, and implementing CI/CD for data pipelines.

Nice-to-Have

• Experience building Real-time Pipelines using Kafka or Flink.

• Familiarity with Data Contracts and Data Quality frameworks (Great Expectations, Monte Carlo).

• Knowledge of Vector Databases (Pinecone, Milvus) for AI/LLM applications.

• Infrastructure as Code (Terraform) experience.

Responsibilities

• Build and maintain scalable, automated ELT/ETL pipelines that provide a "single source of truth" for the organization.

• Implement rigorous automated testing and monitoring to ensure data integrity and reliability.

• Optimize warehouse storage and compute costs while reducing pipeline latency.

• Partner with Data Scientists and Product Managers to translate business requirements into technical data models.

• Promote a "DataOps" culture within the team, conducting code reviews and sharing best practices.

Get paid, not played

No more unreliable clients. Enjoy on-time monthly payments with flexible withdrawal options.

Predictable project hours

Enjoy a harmonious work-life balance with consistent 8-hour working days with clients.

Flex days, so you can recharge

Enjoy up to 24 flex days off per year without losing pay, for full-time positions found through Proxify.

Career-accelerating positions at cutting-edge companies

Discover exclusive long-term remote positions at the world's most exciting companies .

Hand-picked opportunities, just for you

Skip the typical recruitment roadblocks and biases with personally matched positions.

One seamless process, multiple opportunities

A one-time contracting process for endless opportunities, with no extra assessments.

Compensation

Enjoy the same pay, every month with positions landed through Proxify.

Skills

pythonsnowflakeci-cdairflowawsbigquerydbtdockergitkafkallmpandas

Who can apply

The employer didn't state any visa, work authorization, citizenship or clearance requirements in this posting. Confirm with the employer before applying.

Read automatically from the employer's posting text. Always confirm with the employer — requirements can change after a job is published.

Apply