Senior Data Engineer (Python)
Proxify is seeking a senior data engineer to design and scale data foundations for a high-growth client product, with a focus on python and remote work within the CET time zone.
Skills required
About this role
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:
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5+ years of experience building complex data processing applications using Python (Pandas, PySpark, or Dask).
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Advanced SQL skills for complex transformations, window functions, and query optimization in cloud warehouses.
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Deep experience with dbt (data build tool) for managing the T in ELT, including documentation and testing.
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Proven experience with Apache Airflow, Prefect, or Dagster for managing complex dependency graphs.
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Hands-on experience with Snowflake, BigQuery, or AWS Redshift.
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Strong understanding of Dimensional Modeling (Star/Snowflake schema) and Data Vault 2.0.
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Experience with Git, Docker, and implementing CI/CD for data pipelines.
Nice-to-Have:
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Experience building Real-time Pipelines using Kafka or Flink.
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Familiarity with Data Contracts and Data Quality frameworks (Great Expectations, Monte Carlo).
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Knowledge of Vector Databases (Pinecone, Milvus) for AI/LLM applications.
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Infrastructure as Code (Terraform) experience.
Responsibilities:
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Build and maintain scalable, automated ELT/ETL pipelines that provide a "single source of truth" for the organization.
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Implement rigorous automated testing and monitoring to ensure data integrity and reliability.
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Optimize warehouse storage and compute costs while reducing pipeline latency.
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Partner with Data Scientists and Product Managers to translate business requirements into technical data models.
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Promote a "DataOps" culture within the team, conducting code reviews and sharing best practices.
What we offer:
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.
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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.