Senior Agentic Data Engineer (IC3)

Partner with Product Management, Software Engineering, Architecture, Infrastructure, Quality Engineering, DevEx, and other technical leaders to align data solutions with product strategy and organizational priorities.

Lead technical discussions, architecture reviews, cross-team engineering initiatives, and enterprise data integration efforts.

Mentor Data Engineers through technical coaching, design reviews, code reviews, and knowledge sharing while promoting engineering excellence.

Influence engineering decisions by promoting modern data architecture, cloud-native engineering practices, data governance, and operational excellence.

NOTE : This job description is not intended to be all-inclusive. Employees may be asked to perform other related duties as negotiated to meet the ongoing needs of the organization.

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related field, or equivalent combination of education and experience.

5+ years of progressive experience in data engineering, backend software engineering, or cloud-native platform development.

Advanced proficiency in Python and modern software engineering practices, including object-oriented programming, asynchronous programming, type hinting, and application architecture.

Expert experience with SQLAlchemy ORM, Alembic migrations, PostgreSQL, relational database design, and query optimization.

Demonstrated experience designing scalable REST APIs, distributed systems, enterprise data pipelines, and cloud-native applications.

Strong experience designing and implementing ETL/ELT pipelines, data integration solutions, and enterprise data platforms.

Expertise with AWS services, cloud-native architectures, Infrastructure as Code (Terraform or equivalent), CI/CD pipelines, observability, automation, and DevOps practices.

Experience using AI-assisted software development tools and modern engineering practices to improve software quality, developer productivity, and data engineering efficiency.

Proven ability to lead complex technical initiatives, drive architectural decisions, and balance technical tradeoffs with business objectives.

Strong analytical, systems-thinking, and problem-solving skills with the ability to resolve complex technical challenges.

Excellent communication, collaboration, and technical mentoring skills with experience influencing engineering teams and cross-functional stakeholders.

Experience leading enterprise-scale data platform or cloud modernization initiatives across multiple teams.

Deep expertise with Snowflake, modern data warehouses, lakehouse architectures, or large-scale analytics platforms.

Experience designing event-driven architectures, streaming platforms, or distributed data processing systems.

Experience with Infrastructure as Code, Kubernetes, container orchestration, platform engineering, or Site Reliability Engineering practices.

Experience establishing engineering standards, reusable frameworks, shared developer tooling, or data governance practices.

Experience with AI-assisted development, intelligent automation, machine learning pipelines, or AI-enabled data engineering.

AWS certifications, Snowflake certifications, or other cloud and data engineering certifications.

Experience contributing to enterprise architecture, technology strategy, or organizational engineering initiatives.

Experience designing data platforms that support large language models (LLMs), vector databases, Retrieval-Augmented Generation (RAG), semantic search, or AI-powered applications.