Software Engineer, Machine Learning Platform
Leads and grows Data Engineering teams building scalable, governed, AI-ready data foundations and trusted data products. The role requires 7+ years leading Data Engineering teams and experience with technologies including Spark, Snowflake, data lakes, data warehouses, key-value stores, and dbt.
About the job
Responsibilities
- Lead AI-driven, data-centric initiatives that accelerate business growth, improve decision-making, and advance the data platform.
- Partner with Analytics, Product, Data Science, Marketing, and other stakeholders to deliver trusted, secure data products.
- Lead, mentor, and grow high-performing engineering teams while fostering technical excellence, collaboration, innovation, and continuous learning.
- Establish direction and high expectations, champion continuous improvement, and drive operational excellence.
- Prioritize work across teams, resolve issues, remove delivery obstacles, and maintain engineering quality and velocity.
Requirements
- 7+ years of experience leading Data Engineering teams.
- Experience building scalable, AI-ready data tools, semantic models, and trusted data products.
- Strong partnership with Product, Analytics, Data Science, and Marketing teams to deliver business outcomes.
- Experience driving data quality, governance, CI/CD, and operational reliability.
- Experience with Growth and Marketing Data technologies, including attribution, funnels, and experimentation.
- Experience supporting teams using Spark, Snowflake, data warehouses, data lakes, key-value stores, and dbt.
Nice-to-Haves
- Experience with the AWS ecosystem.
- Experience using AI tools to improve engineering productivity.
Compensation and Benefits
- Base salary: $199,000–$275,000 annually.
- Eligible for a bonus, competitive equity package, and benefits.
- Benefits include health, financial, and wellbeing programs; generous vacation and paid days off; wellness stipend; commuter benefits; backup care; and paid parental leave.
Skills
Data Engineering, Spark, Snowflake, Data Warehousing, Data Lakes, Key-Value Stores, dbt, AWS, CI/CD, Data Governance, Semantic Models, AI Tools
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