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Databricks sells the data and AI platform that many large enterprises run their analytics and machine learning on, and this role is the embedded technical advisor for named strategic accounts, working out of Pune within a global capability centre focused field engineering team. You would design lakehouse architectures, help customers evaluate build versus buy for GenAI and machine learning, and implement proofs of concept spanning data engineering, warehousing and AI. It is a long term advisory seat rather than a transactional one: the posting describes building durable relationships with a customer's data, AI and platform engineering leaders and earning a place in their architectural decisions. The bar is high at 12+ years, with 8+ of those hands on with big data and AI technologies including Apache Spark. Who it is for: Asks for 12+ years in data engineering, data science, technical architecture or a similar pre sales or consulting role, and 8+ years of hands on experience with big data and AI technologies including Apache Spark, data engineering, data science and modern AI and machine learning workloads. Day to day: act as trusted technical advisor for one or more named strategic accounts, building durable relationships with their data, AI and machine learning and platform engineering leaders; help shape the customer's AI strategy by working with their data science, machine learning and AI platform teams to design GenAI and machine learning architectures, evaluate build versus buy decisions and move AI ambitions into production; partner with the sales team and provide hands on technical leadership for large enterprise customers across the data and AI lifecycle; consult on modern lakehouse architectures and implement proofs of concept for strategic projects spanning data engineering, data warehousing, machine learning and GenAI, including validating integrations with cloud services, in house tools and third party applications; guide customers through the competitive landscape, best practices and implementation while developing technical champions; and work with the sales team to develop a book of business and define and execute account strategies. The role reports to a Field Engineering Manager and works with product and engineering to influence the Databricks roadmap. Location is Pune, which is a useful data point given how much of this board sits in Bangalore. No office day count and no interview process are published. Fit note: this is a customer facing field engineering role with a book of business and account strategy attached, alongside genuine architecture work. That combination suits people who want to stay deeply technical while working commercially. It does not suit someone looking to write production code every day, and the posting does not pretend otherwise. .
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.