Data Engineer

At Theranica, we are at the forefront of developing innovative, wearable treatments for migraine and other pain conditions, merging cutting-edge technology with patient-centered care.  Our goal is to translate our technological and business knowledge in mobile digital solutions to the field of pain therapeutics.

We offer non-invasive, drug-free, personalized, and affordable wearable therapeutic products for the treatment of pain by integrating the latest neuroscience research with notable technological expertise.

Our collaborative and dynamic work environment fosters creativity and growth, encouraging our team to push the boundaries of medical science. By joining us, you’ll be part of a passionate group dedicated to improving lives through pioneering health solutions.

Position Description

We are looking for a motivated and detail-oriented Data Engineer to join our expanding data team. As a Data Engineer at Theranica, you’ll be more than just a coder- you’ll be the architect of our data ecosystem. You’ll design, build, and optimize the infrastructure that powers our analytics, machine learning, and business insights. Beyond engineering, you’ll be a strategic partner and problem-solver, collaborating with analysts, scientists, and business stakeholders to transform raw data into a reliable and scalable asset.

Roles and Responsibilities

• Design & Build Data Pipelines: Architect, implement, and maintain scalable, reliable ETL/ELT pipelines to support operational and analytical use cases. 
• Data Infrastructure Optimization: Lead initiatives to improve data processing, storage, and retrieval performance across the organization. 
• Data Quality & Governance: Enforce schema evaluation, monitor data completeness and freshness, and ensure integrity across multiple data sources. 
• Modeling & Warehousing: Create and optimize robust data models and warehouse solutions to power BI, analytics, and reporting needs. 
• Cross-Functional Collaboration: Work with product, R&D, analytics, and data science teams to deliver data solutions that drive decision-making. 
• Documentation & Communication: Write clear data definitions, metric logic, and dashboard guides to ensure consistency and transparency. 
• Support Machine Learning Operations (MLOps): Develop infrastructure and workflows to streamline deployment, monitoring, and management of ML models (advantage). 
• Define and enforce best practices for data modelling, pipeline design, and coding standards within the data engineering domain.
• Advise on appropriate tools, technologies, and frameworks for data processing and storage, ensuring alignment with company standards.
• Recommend infrastructure improvements and contribute to the planning of data tools and services.
• Represent the data engineering perspective in cross-departmental projects to ensure scalability, reliability, and compliance.

Qualifications & Requirements

Must Have

• Education- Bachelor’s degree in Computer Science, Engineering (or a related field), or equivalent experience. 
• Experience: 2-4 years as a Data Engineer. 
• Data Expertise: Strong knowledge of data warehousing concepts and methodologies.  
• Proficiency in SQL and Python in production environments.  Hands-on experience with ETL/ELT processes, data modeling, and query optimization. 
• Hands-on experience with CI/CD pipelines and automation. 
• Familiarity with data governance and quality frameworks. 
• Cloud Infrastructure: Proven experience with GCP (BigQuery, Cloud Functions, Cloud Storage); familiarity with other platforms (AWS) is a plus. 
• Soft Skills: Excellent collaboration, analytical thinking, and communication skills. Ability to translate complex data into actionable insights. 

Nice To Have

• Familiarity with MLOps frameworks (e.g., SageMaker, Vertex AI, MLflow). 
• Experience with BI tools (Looker Studio, Power BI, Tableau). 
• Familiarity with healthcare/med-tech data.

Work Environment

Hybrid