Work Hard EverywhereJob Description
Headquarters: Sweden
URL: http://career.proxify.io
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,...
URL: http://career.proxify.io
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,...