Data Engineer II

🕒 August 28

🇪🇸 Spain – Remote

💵 €50k - €74k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 1%

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Logo of Ziff Davis

Ziff Davis

1001 - 5000 employees

Founded 1927

💼 Consulting

🏥 Healthcare

📣 Marketing

💰 $650M Post-IPO Debt on 2017-06

Consulting • Healthcare • Marketing

Ziff Davis is a multi-billion dollar digital media and internet company, home to over 40 leading brands in technology, shopping, gaming and entertainment, connectivity, health and wellness, cybersecurity, and martech. With a focus on mergers and acquisitions, Ziff Davis has deployed around $3 billion in capital, leveraging its deep industry knowledge, technological expertise, and investment acumen. The company is committed to corporate responsibility, emphasizing diversity, equity, and inclusion, as well as environmental, social, and governance practices. Ziff Davis serves millions of customers worldwide, offering a diverse range of digital media and internet services.

📋 Description

• Design and develop high-volume data processing pipelines across Redshift, Athena, Iceberg, Spark, and Airflow • Implement monitoring, alerting, and data quality checks to ensure pipeline reliability and data accuracy • Contribute to architectural decisions and technical design discussions for new data platform initiatives • Participate in code reviews and contribute to team standards for data quality, testing, and documentation • Support and collaborate with data scientists, analysts, product managers, and integrating teams • Develop jobs, libraries, and operations supporting data scientists and analysts working with connectivity performance data

🎯 Requirements

• Bachelor's degree in Computer Science or related field or equivalent experience • 5+ year of professional experience in data engineering • Expertise in SQL and databases (MySQL, Redshift, Athena) • Experience with data modeling • Experience with workflow orchestrators such as Dagster, Airflow, or Prefect • Experience working with Python • Strong communication skills both in person and via virtual mediums • Knowledge of ETL/ELT design patterns • Experience with high volume distributed data processing in Spark • Experience with AWS cloud services • Background check required

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