Senior Data Engineer

Join Sava’s Data Engineering team at a pivotal stage of growth, contributing to the development and scaling of both internal and customer-facing data infrastructures. As a Data Engineer II, you will help implement reliable data pipelines, storage solutions, and reporting systems that power analytical and operational workflows across the company. This is a unique opportunity to work in a multidisciplinary environment, collaborating with a top-tier team in engineering, science, and product to shape the foundation of Sava’s data architecture.

• 
  
• Build and maintain scalable, reliable data pipelines, ensuring efficient and accurate data ingestion, transformation, and delivery.
  
• Design, implement, and optimize data storage solutions using modern databases and cloud-native tools.
  
• Develop and maintain reporting systems and dashboards to support data-driven decision-making.
  
• Collaborate with backend and infrastructure teams to integrate data services with applications and customer-facing tools.
  
• Implement automated testing and validation processes for data workflows and pipelines.
  

• 
  
• 4/5 years of experience in data engineering.
  
• Proficiency in Python.
  
• Strong SQL skills and experience with both relational and non-relational databases (e.g., SQL, MongoDB).
  
• Familiarity with data visualization or reporting tools (e.g., Looker, Power BI, or similar).
  
• Familiarity with containerization and CI/CD tools (e.g., Docker, GitHub Actions).
  
• Knowledge of networking and cloud infrastructure (e.g., AWS, Azure).
  
• Experience with modern data processing frameworks (e.g., dbt, Apache Airflow, Spark, or similar).
  

• 
  
• A strong focus on system observability and data quality.
  
• Emphasis on rapid scalability of solutions (consider market ramp up when entering a new market).
  
• Relentless pursuit of system security.
  
• Adaptable mindset — open to using different tools and approaches depending on project needs.
  
• Ability to work and communicate across disciplines, including Data Science, Mobile Engineering, Embedded Software, Manufacturing, Electronics, Sensor Development, and Mechanical Engineering.
  

• 
  
• Exposure to regulated environments (e.g., healthcare, finance) or compliance frameworks (e.g., HIPAA, SOC2, ISO 27001).
  
• Experience working with data residency constraints and multi-region architectures.
  
• Understanding of secure data handling practices and basic vulnerability concepts.
  
• Familiarity with model-based design approaches, including ER diagrams or data modeling tools.