Senior Data Engineer - Analytics

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Requirements:

• 5 - 8 years of experience in data engineering, analytics engineering, or a related field.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field, with strong coursework in databases, data structures, and system design, or equivalent industry experience.
• Strong proficiency in SQL and Python and experience working with cloud data warehouses (e.g., BigQuery), model analytics pipeline and orchestration tools (e.g., dbt, Dagster, Airflow), and self-service analytics tools (e.g., Looker).
• A solid understanding of analytics database concepts, ELT pipelines, and best practices in data modeling.
• Ability to work cross-functionally with stakeholders to gather requirements and deliver impactful solutions.
• Strong problem-solving skills and a passion for building scalable data solutions.
• [Nice to have] Experience in the healthcare industry or otherwise handling sensitive data.

Responsibilities:

• Design, develop, and maintain ELT data pipelines to ensure reliable and efficient data processing. Our tools include dbt, Dagster, and GCP.
• Build and optimize data models to support analytics and reporting needs.
• Collaborate with analysts and business stakeholders to create and maintain self-service analytics tools that provide meaningful insights. Our primary tools are Looker and Amplitude.
• Ensure data quality and integrity through testing, validation, and documentation.
• Monitor and improve analytics database performance, optimizing queries and warehouse costs. Our analytics database lives on BigQuery.
• Automate and improve our data pipeline workflows for scalability and efficiency.
• Work closely with product, engineering, and business teams to understand data requirements and translate them into effective solutions.