Technical Lead, Data Engineer

Technical Lead, Data Engineer

Department: Research & Development

Employment Type: Full Time

Location: US-California-San Jose

Compensation: $157,050 - $216,000 / year

This position is ideal for senior‑level data engineering professionals to join the Product Analytics team as a Technical Lead, Data Engineer. You will drive the design, development, and management of robust data pipelines, investigate data discrepancies, and enable research through the creation and maintenance of sandbox databases. Partnering with business owners, product engineering managers, functional managers, and cross‑functional teams in R&D, IT, marketing, clinical, and operations, you’ll provide technical leadership and hands‑on expertise to deliver high‑quality, reliable data solutions that support business insights, metrics, and recommendations.

You will operate as a power user of the Datalake, collaborating with partner teams for administrative support and broader data access.

• Serve as the technical leader and subject matter expert for dashboard development, setting best practices for design, implementation, and monitoring of analytics dashboards.
• Lead the investigation and resolution of complex data discrepancies, collaborating with cross‑functional teams to ensure data accuracy, consistency, and integrity across all reporting platforms.
• Architect, develop, and maintain scalable data pipelines and ETL/ELT processes using Databricks, Starburst, and Kafka within the team’s allocated data catalog and resources.
• Design and manage sandbox databases, enabling rapid prototyping and research for internal stakeholders.
• Design and maintain data models and schemas for efficient querying and reporting, utilizing Starburst for federated data access.
• Collaborate with partner teams for data access, integration, and troubleshooting beyond your team’s scope.
• Oversee the extraction, cleaning, wrangling, and exploratory analysis of data using SQL and programming languages (e.g., Python).
• Document technical processes and mentor team members in best practices for data engineering and dashboard development.
• Monitor and optimize data infrastructure performance, troubleshooting issues as needed within the team’s allocated resources.
• Establish and enforce data governance and usage guidelines to ensure compliance and best practices.
• Remain current on industry trends and emerging technologies in data engineering, BI, and analytics.

• Education:
  
  BS or MS in Computer Science, Engineering, Data Science, or related technical field.
• Experience:
  
  8-12 years of experience in Data Engineering, Data Analytics, Business Analytics, or related fields.
• Skills:
  
  Strong knowledge of data modeling, ETL, and dashboard development;
  Hands‑on experience with Databricks, Starburst, and Kafka as a power user;
  Hands‑on expertise with dashboard development and monitoring (e.g., Power BI, Tableau);
  Deep expertise in data discrepancy investigation, root‑cause analysis, and resolution;
  Strong analytical and problem‑solving abilities;
  Demonstrable experience designing and managing data pipelines and ETL frameworks;
  Proficiency in SQL writing & optimization, data modeling, and relational database management;
  Proficiency in Python or other programming languages for data engineering tasks;
  Familiarity with cloud data platforms and big data technologies;
  Strong organization and project management skills.
• Communication:
  Exceptional communication and documentation skills to accurately convey technical requirements and priorities to stakeholders.
• Teamwork:
  Ability to work cross‑functionally with a diverse group of people and functions to drive timely solutions.

• Strong presentation and documentation skills.
• Self‑motivated, proactive, and willing to work through barriers and strive for continuous improvement.
• Desire and willingness to develop clinical understanding of Invisalign product and orthodontics.

If provided, base salary or wage rate ranges are the range in which Align reasonably expects to set a candidate’s pay for the posted position. Actual placement depends on the individual skills and experience level of a candidate plus the total…