Staff Data Engineer

2 days ago

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5001 - 10000

💰 Post-IPO Equity on 2020-12

Description

• Architect and productionize batch and real-time data systems to support various products and business needs. • Ensure the quality, performance, and stability of data systems through robust quality systems and monitoring practices. • Design and optimize data models for efficient storage and retrieval to meet critical product and business requirements. • Collaborate with cross-functional teams, including product managers, engineers, data scientists, and business partners, to align on data requirements and develop scalable systems. • Tune, productionize, and optimize data systems and machine learning models to enhance their effectiveness and efficiency. • Build and maintain strong relationships with partner engineering teams, including backend, client, data science, and ML teams, to ensure seamless integration and support. • Contribute to the development of long-term data strategies and roadmaps, and influence the technical direction of data engineering practices within the organization. • Mentor and coach team members, providing guidance and support to enhance their skills and performance.

Requirements

• 9+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience, or 6+ years of experience with a PhD. • Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale. • Strong knowledge of Java, Scala, or Python, and expertise with data processing technologies and query authoring (SQL). • Proven ability to design, productionize, and optimize batch and real-time data pipelines and systems, ensuring their quality, performance, and stability. • Excellent ability to collaborate with cross-functional teams, including product managers, engineers, data scientists, and business partners, to align on requirements and drive data-driven decision-making. • Advanced analytical and problem-solving skills with a focus on data quality, governance, and system reliability. • Exceptional written and verbal communication skills, capable of influencing stakeholders and conveying complex technical concepts effectively. • Expertise in data modeling, warehousing, and working with relational (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery). • Experience working with machine learning engineers to integrate ML models into data systems and products (preferred but optional). • Ability to provide technical leadership and mentorship, guiding teams on best practices and contributing to the development of data engineering strategies. • Flexibility and innovative thinking to evaluate and incorporate new technologies and methodologies to improve data processes and solutions.

Benefits

• Eligible for bonus, equity, benefits, and Employee Travel Credits.