Senior Analytics Engineer

Job Requirements

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.

We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you. The achievers and courageous challenge-crushers we seek, have the following characteristics and skills

What You will Do:

• Architect & Build Data Solutions: Design, develop, and maintain scalable and forward-looking data models using custom Python, DBT, and Airflow solution to obtain the right mix of ETL/ELT pipelines.
• Own the Data Modeling Layer: Serve as the subject matter expert for our DBT projects, establishing best practices for code, testing, and documentation to ensure data quality and reliability.
• Drive Business Impact: Partner closely with AI Engineer, business analysts, and program managers to understand their needs and deliver data solutions that directly inform strategy and decision-making.
• Integrate Diverse Data Sources: Develop processes to extract and integrate data from a variety of sources, including third-party tools, internal/external application databases, and internal/external AI/ML service APIs.
• Champion Data Governance: Implement and uphold data quality standards, and contribute to data governance policies to ensure our data is accurate, consistent, and trustworthy through tools like Collibra and Datahub .
• Lead and Mentor: Act as a technical leader and mentor for other team members, leading high-level discussions on technology strategy, architecture, and best practices.

What You Will Bring:

• 8–10 years of experience in data engineering, analytics engineering, or a related software development field.
• Expert-level proficiency in SQL and experience writing complex, highly-optimized queries.
• Strong programming skills in Python for data manipulation and automation.
• Hands-on, production-level experience with dbt (data build tool).
• Proven ability to translate technical decisions into business impact and articulate complex concepts to cross-functional partners.
• Experience working effectively in a complex, matrixed organization on cross-functional projects.
• Excellent communication and collaboration skills, with a results-oriented mindset and a strong sense of ownership.

Pay Range: $95000-$105000

Compensation decisions are made based on factors including experience, skills, education, and other job-related factors, in accordance with our internal pay structure. We also offer a comprehensive benefits package, including health insurance, paid time off, and retirement plan.

Work Requirements:

This role is considered an on-site position located in Sunnyvale, CA, USA

• You must be able to commute to and from the location with your own transportation arrangements to meet the required working hours.
• Shop floor environment, which may include but not limited to extensive walking, and ability to lift up to 40 lbs.

Benefits begin on day one:

• 401(k) matching
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance
• Employer paid Life Insurance, Short- & Long-Term Disability

Work Experience

8–10 years of experience in data engineering, analytics engineering, or a related software development field.

Expert-level proficiency in SQL and experience writing complex, highly-optimized queries.

Strong programming skills in Python for data manipulation and automation.

Hands-on, production-level experience with dbt (data build tool).

Proven ability to translate technical decisions into business impact and articulate complex concepts to cross-functional partners.

Experience working effectively in a complex, matrixed organization on cross-functional projects.

Excellent communication and collaboration skills, with a results-oriented mindset and a strong sense of ownership.

Bonus Points:

Significant experience with cloud data warehouses and platforms, especially AWS (Redshift, S3, Glue).

Experience building and consuming APIs, particularly with frameworks like FastAPI.

Familiarity with interacting with external AI/ML models or