Senior Data Engineer

LifeStance Health is a leading mental health practice group dedicated to helping individuals and communities with their mental health needs. The Senior Data Engineer will be responsible for building, maintaining, and optimizing cloud-based data solutions to support data-driven decision-making, collaborating closely with data analysts and software engineers.

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, 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
• 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
• 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

Requirements:

• 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
• 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