Staff Data Engineer
IN-Remote
India Careers
Req #: 16963
Type: Regular
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Overview: Lead the design and delivery of Avalara's AI-enabled data platform. You'll build scalable data pipelines, shared data models, and production AI workflows that power both customer-facing products and internal decision-making. This role operates as a senior individual contributor in a player-coach model, combining hands-on engineering with technical leadership and mentorship. This is a hands-on Staff role with technical leadership responsibilities - setting direction, mentoring engineers, and building systems using Snowflake, DBT, and AI capabilities like LLMs and Snowflake Cortex. our work will directly influence how Avalara delivers trusted insights, improves operational efficiency, and scales its compliance platform. Responsibilities: * Design and build scalable data pipelines and shared semantic models using SQL, Python, DBT, Snowflake, Airflow, and AWS * Develop AI-enabled data quality frameworks using DBT, including automated rule generation, anomaly detection, and documentation * Build and deploy LLM-based solutions such as Retrieval-Augmented Generation (RAG) pipelines and agentic workflows using Snowflake Cortex * Architect AI-native data pipelines that integrate LLMs, vector search, and orchestration frameworks * Partner with engineering, product, and business teams to define metrics, enforce governance, and ensure data reliability * Lead architecture decisions, conduct design reviews, and contribute hands-on to critical systems * Mentor engineers and raise the technical bar across the team * Translate complex data and AI outputs into clear insights that influence business decisions Qualifications: * Bachelor/master's degree in computer science or engineering * 9+ years of experience building large-scale data systems in cloud environments * Expert-level SQL and Python for building pipelines, data models, and automation frameworks * Hands-on experience with Snowflake, DBT, Airflow, and AWS, including AI/ML integration * Experience building and deploying LLM-based systems such as RAG pipelines and prompt-driven workflows * Proven ability to define shared metrics and build semantic layers used across teams * Strong technical leadership skills, including mentoring and influencing cross-functional partners
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