Senior Data Engineer

3 weeks ago

London, Greater London, United Kingdom Partnerize Full time

Who We Are:

Partnerize is a performance marketing technology company that empowers marketers to discover, engage, and convert audiences at scale. Our platform leverages automation and data-driven insights to deliver exceptional results for our clients.

Why Partnerize?

At Partnerize, we believe in fostering a culture of collaboration, innovation, and growth. We are committed to attracting and retaining top talent who share our passion for excellence. Joining our team means becoming part of a dynamic and supportive environment where your contributions are valued.

The Data-Driven Heart of Our Business:

We operate at the forefront of performance marketing, constantly analyzing vast amounts of data to optimize campaigns and drive success. As a leading provider of data-driven solutions, we rely on talented engineers like you to build and maintain our robust data infrastructure.

Your Role as a Senior Data Engineer:

  • Design, develop, and maintain scalable data pipelines using cutting-edge technologies such as Google Cloud Platform, BigQuery, Apache Airflow, Airbyte, HDFS, Kafka, and Spark.
  • Integrate diverse data sources from both internal and external systems to create a comprehensive view of our business operations.
  • Ensure the reliability, performance, and security of our data systems by implementing best practices for data quality, governance, and access control.
  • Collaborate closely with cross-functional teams, including data scientists, product managers, and engineers, to understand business requirements and translate them into technical solutions.
  • Contribute to the development of innovative data models and algorithms that empower our clients to make informed decisions.
  • Stay abreast of emerging trends and technologies in the data engineering landscape to continuously enhance our capabilities.

Your Expertise:

  • Proven experience with Google Cloud Platform, BigQuery, Apache Airflow, Airbyte, HDFS, Kafka, and Spark.
  • Strong understanding of data warehousing principles, ETL processes, and data modeling techniques.
  • Proficiency in Python for developing production-ready code and scripting.
  • Solid knowledge of SQL and query optimization strategies.
  • Commitment to data security and privacy best practices.
  • Excellent problem-solving, analytical, and communication skills.

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