About the Role

We are looking for a Data Engineer II to help design, build, and maintain the scalable data infrastructure that powers clinical and operational decision-making across InStride. In this role, you will develop and own reliable ETL/ELT pipelines, contribute to our data warehouse architecture, and partner closely with our analytics and business intelligence teams to ensure high-quality, trusted data reaches every corner of the business. This is a high-impact, hands-on engineering role for someone who takes pride in building systems that are not just functional, but resilient, observable, and built to scale. This role reports to the Director of Data Engineering and is a fully remote position.

Responsibilities

• Design, develop, and maintain robust, scalable ETL/ELT data pipelines using Python, SQL, and data processing frameworks including dbt, Matillion, and AWS services.
• Implement data quality checks, monitoring, and alerting across all data pipelines to ensure data integrity and reliability.
• Optimize existing pipelines for performance, cost-efficiency, and error handling.
• Contribute to the design and maintenance of InStride’s data warehouse and data lake solutions, including schema design, data modeling, and indexing strategies in Amazon Redshift.
• Ensure data security, HIPAA compliance, and proper handling of protected health information (PHI) within all data infrastructure.
• Work closely with data analysts, data scientists, and business intelligence engineers to understand their data requirements and deliver reliable, high-quality data access.
• Troubleshoot and resolve complex production data issues with urgency and root-cause rigor.
• Develop and maintain clear documentation for data models, pipelines, and data sources to enable self-service analytics.
• Participate in code reviews and contribute to technical discussions, bringing a constructive and detail-oriented perspective.
• Stay current on emerging data technologies and tools, bringing relevant insights to the team.

What You Need to Succeed in the Role

• 3+ years of experience designing, developing, and deploying data pipelines and data warehouse solutions in production environments.
• Strong proficiency in SQL and Python for data engineering and transformation work.
• Hands-on experience with cloud data warehouses (Amazon Redshift preferred; Snowflake or BigQuery also valued) and familiarity with ETL/ELT tools such as dbt, Matillion, or similar.
• Working knowledge of AWS services relevant to data engineering (e.g., S3, Glue, Lambda, Redshift).
• Demonstrated understanding of HIPAA compliance requirements and experience working with sensitive or regulated data.
• Ability to design and build data systems that are scalable, observable, and built to handle growth in data volume and complexity.
• Strong understanding of data integration patterns, including APIs, webhooks, and batch ingestion techniques.
• Experience giving and receiving structured feedback through pull request reviews and technical discussions.
• Strong communication skills, with the ability to translate complex technical concepts for both technical and non-technical stakeholders.
• Comfortable operating in a fast-paced startup environment, balancing competing priorities and making sound tradeoffs.
• Experience working with healthcare data is a plus.

The expected annual salary for this role is between $110,000–$125,000. Actual starting salary will be determined on an individualized basis and will be based on several factors including but not limited to specific skill set, work experience, etc.