Senior Data Engineer

About LifeStance

At LifeStance Health, we strive to help individuals, families, and communities with their mental health needs. Everywhere. Every day. It’s a lofty goal; we know. But we make it happen with the best team in mental healthcare. Thank you for taking the time to explore a career with us. As the fastest growing mental health practice group in the country, now is the perfect time to join our team!

LifeStance Health Values

• Belonging: We cultivate a space where everyone can show up as their authentic self.
• Empathy: We seek out diverse perspectives and listen to learn without judgment.
• Courage: We are all accountable for doing the right thing – even when it’s hard – because we know it’s worth it.
• One Team: We realize our full potential when we work together towards our shared purpose.

Benefits

As a full-time employee of LifeStance Health, the following benefits are offered: medical, dental, vision, AD&D, short and long-term disability, and life insurance. Additional benefits include a 401k retirement savings with employer match, paid parental leave, paid time off, holiday pay and an Employee Assistance Program.

Role Overview

The Senior Data Engineer will play a key role in building, maintaining, and optimizing cloud-based data solutions that support data-driven decision-making at LifeStance. This role requires expertise in AWS data services (Glue, Redshift, Lambda, S3, Kinesis), SQL, Python, Apache Spark, and PostgreSQL, with a focus on scalability, performance optimization, and real-time processing. You will work closely with data analysts, business intelligence teams, and software engineers to ensure data integrity, governance, and efficiency, while also serving as a production support lead for troubleshooting and maintaining high availability of our data infrastructure.

Compensation

$110,000 – 135,000/annually, plus annual bonus potential

Challenges & Opportunities

• Scalable Data Infrastructure – Design and optimize AWS-based data pipelines for structured and unstructured data processing.
• Real-time & Batch Processing – Develop robust ETL/ELT pipelines leveraging Apache Spark, AWS Glue, and Kinesis.
• Production Support & Issue Resolution – Lead real-time monitoring, troubleshooting, and optimization of data pipelines.
• Data Warehousing & Performance Optimization – Optimize PostgreSQL, Redshift, and S3-based data lakes for high performance.
• Cost-efficient Data Engineering – Improve cost-efficiency and scalability of cloud data infrastructure.
• Data Governance & Compliance – Implement security, compliance, and governance frameworks aligned with HIPAA, GDPR, and SOC2.

Responsibilities

• Provide primary data engineer for real-time production support, ensuring minimal downtime of mission-critical data pipelines.
• Rotate the role and on call requirements.
• Monitor, troubleshoot, and optimize data pipeline failures, query performance bottlenecks, and data discrepancies using AWS CloudWatch.