Senior Data Engineer

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September 20

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Vantage Data Centers

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Enterprise

Vantage Data Centers is a company specializing in the design, development, and operation of highly flexible and scalable data centers. These data centers cater to hyperscalers, cloud providers, and large enterprises, offering state-of-the-art facilities across 5 continents and 21 markets. Vantage focuses on providing large-scale campuses that enable customers to grow steadily, with over 23 million square feet dedicated to data center space and 2. 6GW+ of power capacity. Committed to sustainability and efficiency, Vantage ensures 100% uptime with standardized designs offering predictability and performance. The company is backed by prominent investors such as DigitalBridge Group and Silver Lake, maintaining a strong financial standing and excellent customer satisfaction rates.

1001 - 5000 employees

Founded 2010

🏢 Enterprise

📋 Description

• Design data infrastructure to collect, process, and analyze massive retail media datasets • Use real-time and batch processing technologies to push the boundaries of data processing at scale • Lead architectural conversations and guide development of data infrastructure to ensure availability of high-quality, trustworthy data • Oversee processing and transformation of data and ensure proper data hygiene for downstream applications • Write maintainable Python code to deliver high-quality, scalable data management solutions • Document new and existing features clearly to support team alignment and future development • Coach and develop the Measurement team to raise collective capability and drive long-term growth • Communicate with stakeholders across the organization to align expectations and ensure transparency regarding data infrastructure and management

🎯 Requirements

• 5+ years of experience working in data engineering, big data, and/or distributed systems for SaaS (Software as a Service) products • Proficiency with Python, Django, and SQL • Hands-on experience using Snowflake to build ETL/ELT pipelines, data-warehousing, and analysis • Hands-on experience using Great Expectations to test and validate data quality, or a similar data testing tool • Hands-on experience with data modelling, data warehousing, and distributed systems • Experience with privacy-compliant data processing (GDPR, CCPA) for advertising/retail media use-cases • Track record of successful collaboration with other engineering and product teams • Familiarity with managing real-time streaming data using tools such as Kafka, Kinesis, and/or Pub/Sub • Bonus: Hands-on experience with data lakes and ML (Machine Learning) pipelines • Legally authorized to work in Canada (application asks for confirmation) • Successful completion of a criminal background check required in final stages of hiring

🏖️ Benefits

• Remote-first work environment • Flexible work philosophy • Remote-friendly setup • Home office support • Annual company retreats • Equal opportunity employer committed to diversity, equity, and inclusion • Reasonable accommodations available to applicants on request