Full Stack Data Engineer : 26-02060

Akraya, Inc.; Santa Clara (CA); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Akraya, Inc. in Santa Clara, CA is seeking a Staff Data Engineer, Full Stack, to design and build scalable data platforms while driving AI/ML initiatives that deliver actionable business insights.

This hybrid role blends data engineering and data science to deploy production ML models and enable customer analytics across the enterprise. You will design data architectures, build batch and real-time pipelines on GCP (BigQuery, Vertex AI), develop feature pipelines, and create dashboards with

Qualifications

• 8+ years of experience in Data Engineering, Data Science, or Analytics Engineering.
• Expert-level programming skills in Python and advanced SQL.
• Experience with GCP (BigQuery, Vertex AI) and cloud data architectures.
• Experience building scalable data pipelines for analytics and ML.

Responsibilities

• Design, develop, and maintain scalable data architectures and analytical datasets for reporting, BI, and ML.
• Build and optimize batch and real-time data pipelines using cloud-native technologies.
• Develop, deploy, and monitor ML models for customer analytics and business optimization.
• Design feature engineering pipelines and support end-to-end AI/ML lifecycle from development through production.
• Implement AI-powered solutions and optimize Generative AI/LLM-based applications.
• Collaborate with product, GTM, CS, Finance, and Engineering to translate business challenges into data-driven solutions.
• Develop dashboards and visualizations using Tableau, Looker, or similar BI tools.
• Perform code reviews and improve engineering practices for scalable cloud data platforms.

Skills

Python

SQL

Data pipelines

Cloud platforms

BigQuery

Vertex AI

BI dashboards

Python advanced

Education

MS/PhD in CS/AI/Data Science

Tools

Tableau

Looker

Job description

Overview

Staff Data Engineer, Full Stack to design and build scalable data platforms while driving AI/ML initiatives that deliver actionable business insights. This hybrid Data Engineering and Data Science role requires expertise in data pipelines, cloud-based analytics, machine learning, and generative AI to develop robust analytical datasets, deploy production-grade ML models, and enable customer analytics solutions across the enterprise.

Responsibilities

• Design, develop, and maintain scalable data architectures and analytical datasets for reporting, business intelligence, and machine learning.
• Build and optimize batch and real-time data pipelines using cloud-native technologies.
• Develop, deploy, and monitor machine learning models for customer analytics, churn prediction, marketing attribution, and business optimization.
• Design feature engineering pipelines and support end-to-end AI/ML model lifecycle from development through production.
• Implement AI-powered solutions and optimize Generative AI/LLM-based applications and AI agents.
• Partner with Product, GTM, Customer Success, Finance, and Engineering teams to translate business challenges into data-driven solutions.
• Develop dashboards and visualizations using Tableau, Looker, or similar BI tools.
• Perform code reviews, improve engineering best practices, and support scalable, secure cloud-based data platforms.

Qualifications

• 8+ years of experience in Data Engineering, Data Science, or Analytics Engineering.
• Expert-level programming skills in Python and advanced SQL.
• Strong experience designing and maintaining scalable data pipelines for analytics and machine learning.
• Experience implementing Big Data solutions for batch and real-time processing.
• Hands-on experience with Google Cloud Platform (GCP), including BigQuery and Vertex AI.
• Experience building optimized analytical datasets for reporting, feature engineering, and business intelligence.
• Experience developing dashboards using Tableau, Looker, or similar visualization platforms.
• Strong knowledge of cloud data architecture, ETL/ELT frameworks, and data modeling.
• Excellent analytical, problem-solving, and stakeholder communication skills.

Nice-to-have

• Experience with Generative AI, LLMs, LangChain, LlamaIndex, or Hugging Face frameworks.
• Experience evaluating and optimizing AI agents and conversational AI systems.
• Knowledge of causal inference, time-series forecasting, and advanced statistical modeling.
• Experience implementing data security, governance, and role-based access controls.
• Background in Customer Analytics, Customer Success, Marketing Analytics, or Professional Services.
• Experience with streaming technologies and modern data orchestration frameworks.

Preferred Qualifications

• MS or PhD in Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field.
• Proven experience delivering end-to-end AI/ML solutions in cloud environments.
• Experience working in Agile environments with modern software engineering and DevOps practices.
• Strong ability to lead technical initiatives, work independently, and drive projects from concept through production deployment.