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Careers Open role Senior Data & AI Engineer Design, build, and scale modern data and AI solutions on Snowflake, turning complex business operations into trusted, production-ready systems. Full-time· Remote (Americas) ← Back to all roles About The Role At Viewnear, we help enterprises stand up two capabilities they keep: a data practice their teams trust and an AI practice that ships use cases into production, built on Snowflake, run by the client's own team, and guided and accelerated by ours. We're looking for a Senior Data & AI Engineer who brings strong technical depth, ownership, and execution discipline to the data and AI practices we build with clients. This role is for someone who knows that great data and AI work is not built through big talk. It is built through clean architecture, reliable pipelines, thoughtful modeling, strong engineering habits, and the willingness to solve complex problems when the path is not perfectly clear. The role helps design, build, and scale modern data and AI solutions on Snowflake, turning complex business operations into trusted, usable, production-ready systems. What the role involves This engineer leads the design and implementation of governed data foundations, pipelines, data models, and AI-ready architectures using Snowflake as the core cloud data platform. The work runs close to business, analytics, engineering, and leadership teams: understanding operational challenges, translating them into technical requirements, and delivering solutions that create measurable business value. It also means bringing AI use cases from concept to production: preparing trusted data, building scalable integration patterns, and supporting solutions such as LLM applications, RAG architectures, semantic search, automation workflows, and AI-powered analytics. This is a hands-on role: writing SQL and Python, designing data models, building ELT pipelines, reviewing technical designs, troubleshooting performance issues, documenting decisions, and mentoring others on the team. What we're looking for Strong Experience Across Snowflake architecture, development, performance tuning, cost optimization, and security Data engineering with SQL, Python, Snowpark, Snowflake Cortex, Tasks, Streams, Dynamic Tables, and Stored Procedures ELT pipeline design, data modeling, dimensional modeling, semantic layers, and analytics engineering Data integration patterns using APIs, files, external stages, cloud storage, and orchestration tools AI and ML enablement: trusted data pipelines, vector search, RAG patterns, LLM integrations, and production AI workflows Building production-grade systems with testing, monitoring, governance, access control, documentation, and cost awareness Working directly with business stakeholders to clarify needs and turn them into practical technical solutions Leading technical conversations without ego and raising the quality bar for the team Experience with dbt, Airflow, Coalesce, Azure, AWS, or GCP is a plus. The kind of person who succeeds here The people who thrive here are the ones who keep showing up. They take ownership of messy source systems, unclear requirements, broken pipelines, performance bottlenecks, and ambitious goals, then work through them with patience and precision. They do not need everything to be perfect before starting. They know how to ask the right questions, make smart tradeoffs, and move the work forward. They care about clean architecture, but they care just as much about getting useful solutions into people's hands. They understand that trust in data is earned one correct number, one reliable pipeline, and one well-built solution at a time. They bring technical depth, and just as much humility. They help others get better. They make the team stronger. What success looks like Success means our clients trust their data, AI use cases move beyond demos, pipelines run reliably, and business teams make faster, better decisions. This role helps build the governed foundation on Snowflake that turns ambitious ideas into real systems. We're looking for someone ready to do the work, carry responsibility, and help the team win. Skills & tools SnowflakeSQLPythonSnowparkCortexRAG & LLMsdbtData modeling Life at Viewnear More than the role This is a team judged on outcomes, working AI-native, pairing two hubs with remote depth. Here is some of what comes with the role. Health№ 01 Health insurance Comprehensive medical coverage for the whole family. Health№ 02 Dental & vision Optional dental and vision plans for the everyday essentials. Wellness№ 03 Emotional wellness Optional mental-health and emotional-wellbeing support, because demanding work needs real balance. Balance№ 04 Flexible time off Time off follows local law and stays flexible (no fixed cap) as long as outcomes stay strong and teams stay covered. Growth№ 05 Learning & certifications Training, SnowPro certifications, conference travel, and event sponsorships: we reinvest in the team's growth. Together№ 06 Team retreats Company retreats and in-person gatherings that build the relationships behind great delivery. Tooling№ 07 The tools to do the work Modern hardware, paid AI tooling, and the licenses each project needs, from day one. See life at Viewnear→ Apply Apply for this role Share a few details and we will review the application. We read every one. Apply now Applying for: Senior Data & AI Engineer Website Fields marked * are required. Full name * Email * LinkedIn profile About the candidate * Resume (PDF or Word, max 8 MB) Let's stand up a lasting data & AI practice. Tell us where the organization stands (migrating, scaling, or shipping AI) and we'll map the fastest path to use cases in production, run by in-house teams. Talk to an architectExplore services
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.