What You'll Do
Lead the development of a high-performing data engineering team by mentoring individuals, supporting career growth, and cultivating a collaborative, learning-focused culture. Play an active role in building and refining scalable data platforms and pipelines, contributing directly to architecture and implementation.
Guide the evolution of engineering standards that emphasize quality, reliability, and maintainability. Work closely with Product, Analytics, and Applied Science teams to define priorities and deliver data capabilities that power analytics and machine learning initiatives. Ensure systems are observable, secure, and compliant with governance requirements.
Communicate effectively with technical and non-technical stakeholders, providing clear updates on progress, risks, and strategic direction.
Requirements
- Minimum of two years of experience managing data or software engineering teams
- Proven track record building and maintaining large-scale data processing systems
- Strong proficiency in Python and SQL
- Experience with lakehouse technologies including Delta Lake or Apache Iceberg
- Familiarity with platforms such as Databricks or Snowflake
- Solid foundation in software engineering practices, including CI/CD automation
- Excellent communication, collaboration, and decision-making abilities
Preferred Qualifications
- Background with distributed processing frameworks like Spark or Flink
- Experience developing self-service analytics platforms or internal data tools
- Understanding of AI/ML workflows and the data needs for model development
Technical Stack
Python, SQL, Delta Lake, Apache Iceberg, Databricks, Snowflake, Spark, Flink
Benefits
- Competitive base salary
- Annual performance bonus
- Long-term incentives
