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Senior Data Engineer
HybridFull-timeData EngineeringMental Health Care
Join a behavioral health technology company as a Senior Data Engineer responsible for designing, building, and operating scalable data systems that support analytics, machine learning, and product decision-making. The role combines hands-on engineering with mentoring and technical guidance in a high
Responsibilities
- Design and maintain reliable, distributed data infrastructure and exploratory data analysis tooling
- Build and operate batch and real-time ETL pipelines for structured and unstructured data
- Design data models and data warehouses using SQL and NoSQL systems
- Productionize machine learning models and build supporting tools
- Manage data processing, storage, governance, performance, and quality
- Optimize data systems for performance, cost, scalability, and reliability
- Enable researchers, data scientists, analysts, and product teams to use data effectively
- Monitor systems, troubleshoot issues, and identify process improvements
- Write clean, maintainable object-oriented code
- Mentor data analysts and guide engineering practices
Requirements
- At least 5 years of experience with large-scale data processing and distributed systems
- At least 5 years of development experience in Python or another general-purpose programming language
- At least 3 years of SQL experience
- Experience building a data lake or data warehouse with a data analytics platform
- Experience with Airflow or another orchestration and scheduling framework
- Knowledge of storage services, microservices, security features, and automation tools
- Strong problem-solving, communication, collaboration, and self-learning skills
Nice to have
- Experience with Spark, Flink, or MapReduce
- Experience working with AWS
- Experience with Docker, Kubernetes, and Terraform in data engineering contexts
Benefits
- Significant equity
- Hybrid work opportunities
- Mental health days
- Opportunity to influence technology that improves therapy effectiveness