Lead Data Architect

Summary

Join Milk Moovement as a Data Architect and oversee the evolution of our data platform, including the data warehouse, transformation pipelines, and cloud infrastructure. You will develop and maintain data architectures, supervise business analytics and reporting, and collaborate with feature teams to ensure scalable data models. This role requires at least 5 years of data engineering experience with specific expertise in Snowflake and dbt. You will also mentor data engineers and ensure alignment with best practices. Milk Moovement offers competitive salaries, equity, unlimited paid vacation, comprehensive health benefits, remote work options, flexible hours, and various other perks. We are committed to building a diverse and inclusive workplace.

Requirements

• Proven track record of deploying large-scale data platforms, with specific experience in Snowflake
• Familiarity with dbt for data transformation and Dagster (or other tools) for pipeline orchestration
• Solid fundamentals in data warehousing concepts and transformation design patterns (real time, batch, event-driven workflows)
• Hands-on experience building cloud native data solutions in AWS
• Proficiency in SQL and Python
• Experience using Terraform to build data infrastructure, deployed via CI/CD pipelines
• Ability to collaborate, prioritize, and deliver value in a dynamic workplace
• At least 5 years prior experience with data engineering

Responsibilities

• Develop new and maintain existing data architectures to support internal and external customer analytics as well as AI/ML workloads
• Supervise business analytics and reporting efforts both internally and for our external cooperative customers
• Participate in design sessions with our logistics and financial feature teams to ensure data models for new products are scalable and extensible
• Collaborate with the broader team to enable AI feature engineering, model training, and deployment at scale
• Provide mentorship to ensure alignment with data engineer best practices

Preferred Qualifications

• Background in MLOps and productionizing AI/ML models. Experience with implementing ML models in Snowflake is considered a bonus
• Exposure to common ML Frameworks (TensorFlow, MLlib, PyTorch, or Scikit-learn)
• Experience using container-based services (Docker, ECS, Kubernetes)
• Experience building real-time transformation systems (Flink, Kafka Streams)
• Experience designing and building data pipelines that integrate and process data from both document-oriented NoSQL and relational SQL databases

Benefits

• Competitive salaries
• Equity - Stock option plan on a standard 4 year vesting schedule with a 1 year cliff
• Unlimited paid vacation and flex time
• Health (mental & physical), dental, & HSA coverage across North America
• Remote work environment
• Flexible hours
• Tools
• Quarterly culture events