[Remote] Sr. Data Engineer I

Note: The job is a remote job and is open to candidates in USA. iHerb is on a mission to make health and wellness accessible to all, and they are seeking a Senior Data Engineer to help evolve and scale their modern data ecosystem. The role involves collaborating with data scientists and analytics engineers to deliver high-quality data and operationalized machine-learning solutions.

Responsibilities

• Designs and builds scalable data extracts, integrations, transformations, and data models
• Ensures successful deployment and provisioning of data solutions across required environments
• Designs and implements data architectures and applications that enable speed, quality, and operational efficiency
• Interacts with cross-functional stakeholders to gather and define requirements and translate them into technical designs
• Develops deep familiarity with enterprise datasets, builds domain knowledge, and advances data quality
• Reviews requirements, identifies gaps, and drives resolution with stakeholders
• Identifies and recommends continuous improvement opportunities, ensuring integrations are automated, governed, and observable
• Serves as a key team member in designing and deploying a ground-up cloud data platform and pipeline
• Partners with data scientists to design, build, and maintain reproducible machine-learning pipelines, including feature engineering, model training, validation, deployment, and monitoring
• Implements CI/CD for data and ML workflows (model packaging, automated testing, environment management, release automation)
• Builds and maintains production-grade ML infrastructure such as feature stores, model registries, data versioning, and experiment tracking frameworks (e.g., MLflow)
• Ensures ML models follow best-practice governance, including automated model performance monitoring, drift detection, logging, observability, and alerting
• Designs scalable data pipelines optimized for ML workloads, such as batch, streaming, and real-time inference use cases
• Establishes MLOps standards, coding practices, and automation patterns that scale across teams

Skills

• Bachelor or Master`s degree in technical discipline such as Computer Science, Information Systems or another technical field
• People person, team player with a strong can-do mentality
• 5+ years of experience as a Data Engineer within a data and analytics environment
• Strong interpersonal skills with a collaborative, proactive, and solution-driven mindset
• Proficiency in data modeling concepts and techniques
• Expertise with Databricks and other cloud data warehousing solutions such as S3, Redshift, or BigQuery
• Hands-on experience building data pipelines and ETL/ELT workflows using PySpark for semi-structured data (merge, delete, combine, wrangling)
• Advanced knowledge of Python and advanced working SQL skills including query optimization
• Ability to write, test, and debug RESTful APIs
• Experience working in agile, cross-functional environments
• Strong analytical, problem-solving, and critical-thinking capabilities
• Ability to guide junior engineers and contribute to technical design reviews
• Strong communication skills with the ability to present complex concepts clearly
• Experience in data quality initiatives such as Master Data Management (MDM)
• Experience operationalizing machine-learning models in production environments
• Hands-on experience with ML tooling such as MLflow, SageMaker, Databricks ML, Kubeflow, or similar
• Experience implementing CI/CD pipelines for data and ML workloads, including automated testing, deployment pipelines, and environment configuration
• Understanding of model lifecycle management, data versioning, feature store design, and model monitoring concepts
• Experience containerizing ML workloads using Docker and deploying them via cloud-native services or orchestrators
• Familiarity with monitoring frameworks, experiment tracking, and performance observability for ML models
• DevOps experience with CICD & unit/integration testing, Docker containerization, workflow orchestration
• Highly Desired AWS certifications (any)
• Databricks certifications – Associate/Professional
• AWS Certified Solutions Architect – Associate/Professional
• AWS Certified Developer – Associate/Professional
• AWS Certified DevOps Engineer
• AWS Certified Solutions Architect
• AWS Certified Data Analytics
• AWS Certified Security - Specialty
• AWS Certified Cloud Practitioner

Benefits

• Medical
• Dental
• Vision
• Basic life insurance
• 401(k) plan
• Time Off
• Paid Sick Leave
• Paid holidays
• Restrict Stock Units
• Annual bonuses

Company Overview

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