Data Engineer

2 weeks ago

Irving, United States Steer Health Full time

Steer Health transforms healthcare with the industry's most widely adopted Al-fueled patient experience and growth.

At Steer Health, we're creating next-generation consumer engagement experiences with solutions spanning care communication, patient engagement, scheduling, smart notifications, and more.

We're growing rapidly and are seeking a highly motivated, Data Engineer to join our dynamic SaaS team. As a Data Engineer, you will play a crucial role in designing, building, and maintaining robust data pipelines and infrastructure to support our data-driven initiatives. You will collaborate with cross-functional teams to ensure our SaaS platform leverages data effectively and efficiently.

Data Pipeline Development: Design, implement, and optimize end-to-end data pipelines for collecting, processing, and storing large volumes of data.

Data Modeling and Architecture: Develop and maintain data models and architecture to support analytical processes, ensuring scalability and performance.

Database Management: Manage and optimize databases, both relational and NoSQL, ensuring data integrity, security, and efficient query performance.

ETL Processes: Implement and optimize Extract, Transform, Load (ETL) processes to integrate data from various sources into our SaaS platform.

Cloud Infrastructure: Work with cloud platforms (AWS, Azure, or GCP) to set up and maintain scalable and cost-effective data infrastructure.

Data Quality Assurance: Implement data quality checks and measures to ensure accuracy and consistency of data across the SaaS platform.

Collaboration: Collaborate with data scientists, software engineers, and business stakeholders to understand data requirements and contribute to the development of data-driven features.

Monitoring and Optimization: Monitor data pipeline performance, identify bottlenecks, and optimize processes for better efficiency.

Qualifications and Skills:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
  • 3-4 years of experience as a Data Engineer, preferably in a SaaS environment.
  • Proficiency in programming languages such as Python, SQL, Java, or Scala.
  • Strong knowledge of big data technologies like Apache Spark, Hadoop, and related ecosystem tools.
  • Experience with cloud-based data solutions and services (AWS Glue, Azure Data Factory, Google Dataflow).
  • Familiarity with data governance, security, and compliance standards.
  • Excellent problem-solving and analytical skills.

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