Remote Data Engineer

Description:

• We are seeking a Data Engineer to join our dynamic team.
• The ideal candidate is an enthusiastic problem-solver who excels at building scalable data systems and has hands-on experience with Databricks, Looker, AWS, MongoDB, PostgreSQL, and Node.js.
• You will work alongside sales, customer success, and engineering to design, implement, and maintain a robust data infrastructure that powers our analytics and platform offerings.
• Key Responsibilities include:
  • Designing, building, and maintaining end-to-end data pipelines using Databricks (Spark) for efficient data ingestion, transformation, and processing.
  • Integrating data from various structured and unstructured sources, including medical imaging systems, EMRs, and external APIs.
  • Collaborating with the analytics team to create, optimize, and maintain dashboards in Looker.
  • Implementing best practices in data modeling and visualization to deliver actionable insights.
  • Deploying and managing cloud-based solutions on AWS (e.g., S3, EMR, Lambda, EC2) to ensure scalability, availability, and cost-efficiency.
  • Developing and maintaining CI/CD pipelines for data-related services and applications.
  • Overseeing MongoDB and PostgreSQL databases, including schema design, indexing, and performance tuning.
  • Ensuring data integrity, availability, and optimized querying for both transactional and analytical workloads.
  • Utilizing Node.js to build and maintain RESTful APIs and microservices for data ingestion, transformation, and application integration.
  • Implementing robust error handling, logging, and monitoring frameworks to ensure reliability and transparency.
  • Adhering to healthcare compliance requirements (e.g., HIPAA) and best practices for data privacy and security.
  • Implementing data governance frameworks to maintain data integrity and confidentiality.
  • Working cross-functionally with data scientists, product managers, and other engineering teams to gather requirements and define data workflows.
  • Documenting data pipelines, system architecture, and processes for internal and external stakeholders.
  • Evaluating new technologies and methodologies to enhance data processing performance and scalability.
  • Providing recommendations on emerging trends in data engineering, analytics, and cloud infrastructure.

Requirements:

• Education & Experience:
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • 3+ years of professional experience in data engineering or a similar role.
• Technical Skills:
  • Databricks (Spark): Proven expertise in building large-scale data pipelines.
  • Looker: Experience in creating dashboards, data models, and self-service analytics solutions.
  • AWS: Proficient with core services like S3, EMR, Lambda, IAM, EC2, etc.
  • MongoDB & PostgreSQL: Demonstrated ability to design schemas, optimize queries, and manage high-volume databases.
  • Node.js: Skilled in developing RESTful APIs, microservices, and backend applications.
  • SQL & Scripting: Strong SQL skills, plus familiarity with Python, Scala, or Java for data-related tasks.
• Soft Skills:
  • Excellent communication and team collaboration abilities.
  • Strong problem-solving aptitude and analytical thinking.
  • Detail-oriented, with a focus on delivering reliable, high-quality solutions.
• Preferred:
  • Experience in healthcare or imaging (e.g., DICOM, HL7/FHIR).
  • Familiarity with DevOps tools (Docker, Kubernetes, Terraform) and CI/CD pipelines.
  • Knowledge of machine learning workflows and MLOps practices.

Benefits:

• Health Care Plan (Medical, Dental & Vision) is provided.
• A Retirement Plan (401k, IRA) is available.
• Paid Time Off (Vacation, Sick & Public Holidays) is offered.
• Opportunities for Training & Development are included.
• The option to Work From Home is available.