Staff Data Engineer (AI)

Location: Mountain View, California, or San Diego, California, United States

Salary: $202,500–$274,000 in Mountain View; $188,500–$255,000 in San Diego

Company

hirify.global is a financial technology platform whose products include TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Architect and build fault-tolerant, scalable big-data platforms for high-volume operational and analytics use cases.
• Collaborate with Product Management, Engineering, and Central Data Lake teams to align platform capabilities with current and future requirements.
• Develop architectures for data normalization, lineage, governance, ontology, and discoverability across diverse systems and business units.
• Curate datasets for advanced analytics, Generative AI, Machine Learning, and customer intelligence.
• Establish engineering practices for code reviews, testing, CI/CD, performance, capacity planning, monitoring, alerting, and incident response.
• Mentor junior engineers and promote technical learning and collaborative problem-solving.

Requirements

• 8+ years of experience in product analytics, web analytics, or related data analytics domains.
• Advanced SQL and big-data technology skills, including Redshift, Spark, Hive, or BigQuery, plus experience with BI tools.
• Strong programming skills in Python or Java/Scala.
• Experience engineering data pipelines, workflow orchestration tools, and end-to-end big-data and analytical platforms.
• Understanding of AI-native architectures and Generative AI platforms, including their implications for data, testing, and behavior.
• Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field; a master’s degree is preferred.

Culture & Benefits

• Cross-functional collaboration with technical, business, and product teams.
• Competitive compensation with potential cash bonus, equity rewards, and benefits.
• Fast-paced environment with flexibility to shift priorities.
• Focus on continuous learning, mentoring, and data-driven decision-making.