DataOps integration Engineer

Description:

As a DataOps integration Engineer on Nimble's DataOps team, you'll be the technical bridge between our customers and our platform. You'll work directly with developers, data scientists, and Sales to support enterprise clients - onboarding them onto Nimble's Platform (our AI-based platform for building data pipelines), troubleshooting complex issues, and owning the end-to-end technical delivery of their data solutions.

This is a hands-on, customer-facing role at the core of what Nimble does. You'll manage multiple customer engagements in parallel, get deep into the technical details, and make real decisions that directly affect customer outcomes.

• Serve as the primary technical contact for enterprise customers throughout onboarding, integration, and ongoing delivery
• Design and implement data pipelines tailored to customer use cases using Nimble's AI-based platform
• Troubleshoot and resolve complex technical issues spanning APIs, web structures, proxies, and data quality
• Write and maintain Python scripts and SQL queries to support customer integrations and data transformations
• Leverage AI tools and LLMs to accelerate delivery, automate workflows, and solve novel customer problems
• Collaborate cross-functionally with Product and R&D to surface customer needs and feed them back into the roadmap
• Handle multiple projects simultaneously, keeping stakeholders aligned and delivery on track

• 1+ years experience as an Integration Engineer, Technical Delivery Engineer or similar roles in a B2B SaaS environment
• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
• Understand how the internet works under the hood - think HTML, the DOM, browser developer tools, and how HTTP requests and responses pass data back and forth.
• Coding & API Skills: comfortable writing scripts (especially in Python or JavaScript) to talk to REST APIs, parse JSON data, and manipulate files.
• Understand Networking: You'll need to learn how IP addresses, proxies, and VPNs work, as a big part of the job involves routing web traffic smoothly and handling geo-restrictions.
• Data Basics: knowledge with data warehouse and data lakehouse concepts and platforms (e.g. S3, Snowflake, Databricks, BigQuery, or similar).
• Troubleshooting Skills: When an integration or data pipeline breaks, you need to be eager to dive into logs, figure out exactly why it failed, and clearly explain the fix to a teammate or customer.
• Familiarity with AI/ML concepts and practical experience working with LLMs, AI APIs (OpenAI, Anthropic, etc.), or AI-powered data tools
• Strong written and verbal English — you'll be communicating with technical and non-technical stakeholders daily
• Self-directed and organized; able to operate in a fast-moving environment with shifting priorities

Nice to Have

• Experience building or integrating AI agents, RAG pipelines, or LLM-based workflows
• Experience with data quality management and large-scale datasets
• Familiarity with enterprise data infrastructure or ETL pipelines