Staff Data Engineer

We are looking for an experienced Staff Data Engineer to lead the development of our high-performance data pipelines and scalable APIs using Databricks and Azure. As a key technical leader, you will design, implement, and optimize data infrastructure, ensuring efficient data processing and real-time analytics capabilities. This role requires deep expertise in big data frameworks, distributed systems, and backend engineering, as well as a strong ability to mentor engineers and drive architectural decisions.

Essential Duties and Responsibilities

• Design and Develop Data Pipelines: Design, build, and maintain scalable, high-performance data pipelines and ETL processes on Databricks/Microsoft Azure to acquire, ingest, process, and transform data from various sources into structured, usable formats.
• Azure Data Platform Expertise: Leverage your in-depth knowledge of Microsoft Azure services such as Azure Databricks, Azure Storage, and Azure SQL Database to architect and optimize data solutions.
• Architect and develop large-scale data pipelines in Databricks, leveraging Apache Spark (PySpark/Scala) for batch and streaming workloads.
• Design, implement, and optimize high-performance  APIs to support data access, ingestion, and real-time processing.
• Lead the development of scalable data infrastructure, ensuring reliability, security, and cost efficiency.
• Integrate Databricks with cloud data lakes (Azure Data Lake, AWS S3) and relational/NoSQL databases such as MongoDB & Postgres.
• Data Governance and Security: Implement data governance best practices and ensure data security, compliance and privacy measures are in place to protect sensitive data.
• Optimize Spark jobs for efficiency and cost-effectiveness, implementing best practices for distributed computing.
• Define and enforce data governance, quality, and security standards, including access control, encryption, and compliance.
• Develop event-driven and real-time data processing pipelines using Kafka, Pulsar, or similar messaging systems.
• Drive the adoption of best practices for backend services, ensuring API security, logging, and monitoring.
• Mentor and coach junior and mid-level engineers, providing guidance on system design, performance tuning, and scalable architecture.
• Collaborate with cross-functional teams, including data scientists, software engineers, and DevOps, to enable seamless data-driven decision-making.
• Lead and participate in technical discussions, driving architecture decisions and improving engineering standards.
• Documentation and Training: Create technical documentation, best practices, and guidelines for data engineering processes, as well as provide training to team members.
• Research and Innovation: Stay updated with the latest trends, tools, and technologies in the data engineering field and identify opportunities for innovation and continuous improvement.

The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Minimum 5-7 years of experience in data engineering or related fields with experience on Azure data services and solutions.
• Strong expertise with Databricks and Apache Spark (PySpark or Scala).
• Proficiency in designing and implementing data solutions on the Microsoft Azure platform.
• Experience with creating and deploying microservices (Docker, Kubernetes)
• Strong programming skills in languages like Python, SQL or Scala,
• Excellent verbal and written communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical stakeholders.

Preferred Experience

• Preferred to have expertise in Delta Lake, Apache Iceberg, or similar transactional data lakes.
• Preferred to have experience in API development
• Preferred to have knowledge of GraphQL and gRPC for efficient data API implementations.
• Preferred to have experience working with machine learning data pipelines and feature stores.
• Ability to analyze complex data requirements, troubleshoot issues, and propose innovative data engineering solutions.
• Experience with medical image data such as X-ray, CT,MRI and familiarity with DICOM format is a plus
• Professional-level certifications in Microsoft Azure, such as Azure Data Engineer Associate or Azure Solutions Architect Expert, are highly desirable.
• Proven experience in leading and mentoring a team of junior data engineers or data interns.
• Strong analytical skills are highly desirable.

Education and Experience

• Bachelor’s degree in computer science, or a STEM related field. A master’s degree is preferred.
  
  

For roles based in the United States that require access to hospital facilities, must be eligible for and maintain credentials at all required hospitals, including meeting any applicable physical requirements or vaccination requirements (including the COVID-19 vaccine, as applicable).

ATEC is committed to providing equal employment opportunities to its employees and applicants without regard to race, color, religion, national origin, age, sex, sexual orientation, gender identity, gender expression, or any other protected status in accordance with all applicable federal, state or local laws. Further, ATEC will make reasonable accommodations that are necessary to comply with disability discrimination laws.

Salary Range

Alphatec Spine, Inc. complies with state and federal wage and hour laws and compensation depends upon candidate’s qualifications, education, skill set, years of experience, and internal equity. $140,000 to $160,000 Full-Time Annual Salary