Senior Data Engineer

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:

Production Support & Issue Resolution

• 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, Redshift, and PostgreSQL.

• Automate Root Cause Analysis (RCA) reporting, reducing resolution time by 30%+ through proactive alerting and system monitoring.

• Implement best practices in IAM roles, encryption, and regulatory compliance (HIPAA, GDPR) to ensure data security and governance.

Data Engineering & Platform Optimization

• Design, develop, and maintain scalable ETL pipelines using AWS Glue, Lambda, Redshift, S3, and PostgreSQL.

• Optimize query performance through partitioning, indexing, query tuning, and materialized views, achieving significant performance improvements.

• Implement CI/CD pipelines for automated deployments using AWS CodePipeline, Terraform, and CloudFormation to improve system stability and deployment efficiency.

• Support streaming data pipelines using Kafka, Kinesis, or Spark Streaming for real-time data ingestion and processing.

• Assist in scaling, performance tuning, and automation to optimize data platform efficiency.

Data Analytics & Business Insights

• Collaborate with business intelligence teams and analysts to develop high-quality data models that support analytics and decision-making.

• Build interactive dashboards and reports using Power BI, Tableau, or Looker to enable real-time insights for stakeholders.

• Automate data validation, cleansing, and quality checks, ensuring 99.9%+ data accuracy across critical business functions.

Skills & Experience:

• 5+ years of experience in data engineering, cloud-based data platforms, and big data processing.

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.

• Expertise in AWS services, including Glue, Lambda, Redshift, S3, CloudFormation, IAM, and CloudWatch.

• Strong SQL & Python experience for data transformations, query optimization, and automation.

• Deep knowledge of PostgreSQL, including performance tuning, indexing, query optimization, and schema design.

• Experience with Apache Spark for big data processing and real-time analytics.

• Expertise in ETL frameworks and data modeling (Star Schema, Snowflake Schema, OLAP/OLTP optimization).

• Hands-on experience with Infrastructure as Code (IaC) tools like Terraform, CloudFormation.

• CI/CD expertise with AWS CodePipeline, Jenkins, or GitHub Actions for data pipeline deployments.

• Data security & governance expertise including IAM roles, encryption, and HIPAA/GDPR compliance.

• Proven track record in troubleshooting production issues, conducting root cause analysis (RCA), and improving system performance.

• Experience working in cross-functional teams with business analysts, data scientists, and DevOps engineers.

Preferred Qualifications:

• Master’s degree in Computer Science, Data Engineering, or a related field preferred but not required.

• Experience with streaming data frameworks (Kafka, Kinesis, Spark Streaming).

• Familiarity with advanced analytics frameworks and ML pipelines (MLflow, SageMaker, Feature Stores).

• Certifications: AWS Certified Data Analytics, Google Cloud Professional Data Engineer, or Databricks Certified Data Engineer Associate.

Additional Requirements:

• Must be legally authorized to be employed in the United States.

• LifeStance is an EEO/Affirmative Action Employer. We do not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability, or any other legally protected status.

• Demonstrates awareness, inclusivity, sensitivity, humility, and experience working with individuals from diverse ethnic backgrounds, socioeconomic statuses, sexual orientations, gender identities, and other various aspects of culture.

LifeStance is an equal opportunity employer. We celebrate diversity and are fully committed to creating an inclusive work environment for all our employees.Learn moreabout Diversity, Equity and Inclusion at LifeStance.