This wellness startup company focuses on developing supplements and probiotics aimed at enhancing gut health, improving digestion, and supporting metabolic balance. Leveraging scientific research and personalized data insights, the company tailors its formulations to meet individual health needs.
THE ROLE:
This role will design, build, and optimize the infrastructure required for seamless data flow and analytics. The role involves managing scalable data pipelines, supporting ML initiatives, and ensuring data integrity, making it ideal for a hands-on engineer who thrives in a fast-paced, high-impact environment.
Design, build, and maintain scalable ETL pipelines using tools like DBT, Fivetran, and Airflow
Optimize and manage data warehouse and lakehouse environments on platforms like Snowflake, ensuring data availability, reliability and performance
Implement and manage scalable workflows using Docker, Kubernetes, and other systems to automate data processing
Collaborate with other teams to support ML model deployment in production
Ensure data compliance with standards and regulations (GDPR, CCPA), manage data lineage, and maintain metadata for secure data handling practices
Develop and execute processes for data validation, cleansing, and anomaly detection for data quality assurance
YOUR SKILLS AND EXPERIENCE:
5+ YOE in data engineering
Start-Up or Retail industry experience
Advanced SQL and Python skills
Experience working with a modern data stack (ex: Snowflake, Fivetran, dbt, airflow, etc)
Strong experience with cloud platforms (GCP, AWS, Azure) and tech like Hive, Postgres, Redis
Proven experience working autonomously and spearheading projects with minimal oversight