🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Why N-able At N-able, were not just helping businesses be secure were redefining what it means to be cyber resilient. Our end-to-end platform blends AI-powered capabilities and flexible tech stacks, so customers can manage, secure, and recover with confidence. But the real power behind it all Our people. Were a global crew of N-ablites, who love solving complex problems, sharing knowledge, and delivering solutions that actually make a difference. If you're into meaningful work, fast growth, and a team thats got your back, youll be surrounded by people who believe in what they doand in you. What You'll Do Design and build governed Snowflake Semantic Views (logical tables, relationships, facts, dimensions, metrics, synonyms) as the shared vocabulary AI agents use to answer business questions. Stand up the evaluation harness for the semantic and agentic layer, including golden-question datasets, LLM-as-a-judge scoring, and side-by-side runs that gate every release. Build logging, monitoring, and lineage across the layer; partner with data engineering and governance team members on observability for upstream pipelines and data products. Curate a verified query repository and custom instructions that raise answer accuracy over time. Ship dynamic Streamlit apps and lightweight data products on top of the semantic layer using AI-assisted coding, modernizing legacy Tableau and Power BI dashboards into faster, interactive experiences. Crosstrain BI analysts in each domain to tune, extend and maintain their domain models, building the hub-and-spoke that scales this beyond a single team. Embed governance and data quality by default, partnering with the Data Governance team members to meet certification, stewardship, and CDE requirements. What You'll Bring Deep SQL and dimensional/semantic modeling expertise (facts, dimensions, metrics, conformed entities), with hands-on experience building a semantic layer in Snowflake Semantic Views, dbt Semantic Layer, LookML, or similar. Hands-on Snowflake experience, ideally including Cortex Analyst, Cortex Agents, and Cortex Search, or comparable text-to-SQL and RAG systems, and a working grasp of why grounding LLMs in governed semantics beats pointing them at raw schema. Strong Python and analytics-engineering fundamentals across Snowflake dynamic tables, streams, tasks, Snowpark, Git workflows, CI/CD, and automated testing, with the discipline to ship documented, maintainable, reviewable code. Fluency with AI-assisted coding (Snowflake Cortex Code, Claude Code, or similar) as a daily driver for delivery; spec-driven development experience is a plus. Proven experience evaluating LLM applications in production: test datasets, LLM-as-a-judge or programmatic scoring, and using the results to drive iteration. Familiarity with Monte Carlo or similar data observability platforms is a plus. Experience building dynamic, interactive data apps (Streamlit or similar) on top of a semantic layer, plus enough Tableau and Power BI to migrate what matters and modernize the reporting estate. Strong communication skills with a knack for cross-training peers, able to run working sessions with BI analysts, translate ambiguous business asks into precise, certified definitions, and help peers tune the model confidently. 8+ years in analytics or data engineering, with at least 1 year building semantic models or LLM-grounded analytics, and a track record of shipping data products that other teams reuse. Purple Perks Group Medical , Personal Accident & Term life coverage Generous PTO and observed holidays2 Paid VoluNteer Days per yearEmployee Stock Purchase ProgramFuN-raising opportunities as part of our giving programN-ablite Learning custom learning experience as part of our investment in youThe Way We Work our hybrid working model based on trust and flexibility About N-able At N-able, our mission is to protect businesses against evolving cyberthreats with an end-to-end cyber resilience platform to manage, secure, and recover. Our scalable technology infrastructure includes AI-powered capabilities, market-leading third-party integrations, and the flexibility to employ technologies of choiceto transform workflows and deliver critical security outcomes. Our partner-first approach combines our products with experts, training, and peer-led events that empower our customers to be secure, resilient, and successful. #LI #AS #LI # Hybrid .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.