DevOps Engineer II - DataBricks

This Software Engineer II role builds and maintains foundational infrastructure for petabyte-scale event data storage, querying, and analysis. The engineer develops features end-to-end, working with data platforms like Snowflake, ClickHouse, and Databricks, and handles tens of billions of daily data rows. Requires 2-4 years of full-stack experience and strong data structures knowledge.

This role designs and delivers modern data platforms for clients, primarily on Databricks, combining hands-on engineering with client advisory. The engineer builds end-to-end lakehouse architectures, engineers batch and streaming pipelines, and migrates legacy warehouses to the cloud. The role requires 5+ years of data engineering experience, expert Python and SQL, and a Databricks Data Engineer Professional certification.

This Data Engineer role focuses on building and maintaining data pipelines and infrastructure using Databricks. Responsibilities include developing ETL processes, optimizing data workflows, and ensuring data quality and availability for analytics and business intelligence.

Responsible for infrastructure automation, CI/CD, and cloud operations to support Big Data and marketing platforms.

This role manages customer advertising budgets and optimizes ad performance on Amazon and other e-commerce platforms using CommerceIQ tools. The specialist collaborates with cross-functional teams, performs deep-dive analyses, and adjusts campaigns to meet KPIs, ensuring customer success and retention.

This role leads the design and development of a scalable crawl platform that unifies data across all CommerceIQ product lines. The engineer will own system architecture, drive technical strategy, mentor engineers, and tackle distributed systems challenges, with a focus on reliability, observability, and developer experience. Requires 8+ years of software engineering experience, including 3+ years leading teams, and expertise in distributed systems, with AWS, Spark, and Kubernetes as pluses.

This Machine Learning Engineer III role is responsible for building and scaling ML pipelines and platforms for CommerceIQ's B2B SaaS products. The engineer will deploy ML models in production, including LLMs on GPUs, and own the ML infrastructure roadmap. Key responsibilities include developing end-to-end pipelines, implementing scaling best practices, and managing model performance monitoring.