Senior Data Engineer

Who is Eleos Health?

Today, more people than ever are speaking publicly about their mental health. Whether it's ourselves, our friends and family or even public figures, taking care of your behavioral health is no longer a taboo, it's vital, and it's only human.

Eleos is on a mission to help deliver the world's most effective behavioral care through data, measurement, and personalization. Or simply put, we want to give clinicians the support they need to do the important work only they can do.

What is this opportunity?
We are seeking a Senior Data Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust, scalable, and cost-efficient data infrastructure. In this role, you will directly enable data-driven decision-making and power the development and deployment of advanced AI/ML products at Eleos Health.

You'll work closely with engineering, product, and data science teams to ensure our data platform is high-quality, resilient, and scalable as we grow. As a Senior Data Engineer on our Data Platform team, you will be responsible for delivering reliable, efficient, and consistent data services across the organization. Your work will span batch processing at scale, platform-wide optimization, and AI/ML enablement, including LLM/RAG-based solutions.

Who are you?
You are an experienced data engineer who has worked extensively on data infrastructure and large-scale data platforms in production environments. You have a strong backend foundation and have not simply transitioned from BI into data engineering. You excel at building scalable, maintainable, and cost-efficient systems that serve as the backbone for both analytics and AI/ML features.

You understand the unique challenges of operating large-scale data workloads and are comfortable working with modern data platform technologies, big data batch frameworks, and AI/ML integrations. You're known for your collaborative approach, service-oriented mindset, and ability to deliver high-quality solutions quickly without compromising reliability or performance.

How will you contribute?

• Design, implement, and maintain scalable, reliable data pipelines and platform components to support both operational and analytical use cases, with a strong focus on ML/AI enablement.
  
  
• Build and optimize large-scale batch data processing workflows (e.g., Apache Spark, Airflow) to ensure speed, efficiency, and fault tolerance.
  
  
• Lead cost optimization initiatives for data processing, storage, and infrastructure.
  
  
• Ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions (including RAG).
  
  
• Collaborate with product, engineering, and data science teams to deliver new features rapidly and with technical excellence.
  
  
• Drive platform-wide improvements in observability, reliability, scalability, and performance.
  
  
• Participate in on-call rotations, providing responsive and service-driven support.
  
  
• Support the deployment and integration of LLM/RAG-based solutions and other AI/ML capabilities.
  
  

What qualifications and skills will help you to be successful?

• 5+ years of experience as a data engineer, with hands-on work in designing and operating large-scale data platforms and infrastructure.
  
  
• Strong proficiency in Python and SQL, with proven experience in production environments.
  
  
• Deep understanding of large-scale batch processing and workflow orchestration tools (e.g., Apache Spark, Airflow).
  
  
• Experience with AI/ML-powered products, including LLM/RAG ecosystems and related frameworks.
  
  
• Familiar with or have worked with these technologies (or alternatives):
  
  
  • Data Processing & Streaming: Apache Spark, DBT, Airflow, Airbyte, Kafka
    
    
  • Data Storage: Data Lakehouse architectures, Apache Iceberg, Vector Databases, RDS
    
    
  • Backend & APIs: FastAPI, micro-service architecture
    
    
  • Cloud Infrastructure: AWS stack (S3, Firehose, Lambda, Athena, etc.), Kubernetes (K8s)
    
    
  • Nice-to-Have ML/AI Experience: LiteLLM, Hugging Face, XGBoost, etc.
    
    
• Proven ability to optimize performance, cost, and scalability of data systems.
  
  
• Strong foundation in data governance, quality, security, and observability.
  
  
• Collaborative and proactive in cross-functional settings, particularly when enabling AI/ML initiatives.
  
  

We have:

• A product that positively impacts people's lives every single day.
• A team of amazing people with a shared vision and the infinite drive to make it happen
• We offer significant equity.
• Opportunity to build, grow, and become highly instrumental in shaping how technology can increase the effectiveness of therapy.
• Hybrid work opportunities.
• You can take any moment on mental health days off simply because you need them.