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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You dont just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About Snowflake Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions. We are now a global, world-class organization with offices in more than a dozen countries and serving many more. This role requires in-person attendance in our Pune office at least 3 days per week. Job Description We are looking for an Analytics Engineer to join our growing Finance Analytics Engineering team. In this role, you will drive value and empower decision-making by developing and maintaining the data infrastructure which fuels reporting and analysis for the Finance organization and has a direct impact on Snowflakes success as a company. As an Analytics Engineer, you will be responsible for the following: Use SQL, Python, Snowflake, dbt, Airflow, and other systems while working within an agile development model to build and maintain data infrastructure for use in reporting, analysis, and automation Perform data QA and develop automated testing procedures for use with Snowflake data models Translate reporting, analysis, and automation requirements into data model requirements and specifications Work with IT and other technical stakeholders to source data from key business systems and Snowflake databases Architect flexible, performant data models that will support a wide range of use cases while driving the organization towards single sources of truth Provide input into data governance strategies and frameworks including permissions and security models, data lineage systems, and data definitions Meet regularly with Finance BI and technical leads to define requirements, formulate project plans, provide status updates, and perform user testing and QA Build and maintain user friendly documentation for data models and key metrics Identify weaknesses in processes, data, and systems, and drive organizational improvements within the Analytics Engineering team What You Will Need Required skills: 3+ years of experience working as an analytics, data, or BI engineer Advanced SQL skills with experience standardizing queries and building data infrastructure involving large-scale relational datasets Experience using Python to parse, structure, and transform data Experience with MPP databases such as Snowflake, Redshift, BigQuery, or other relevant technologies Ability to communicate in an effective and efficient manner while working with a wide range of stakeholders Ability to prioritize and execute tasks in a high-pressure, constantly changing environment Ability to think creatively to solve problems An impulse for introducing structure and simplicity into vague, complex problems An obsession for detail and quality An ability to identify weaknesses in data and process, and a willingness to drive improvement A bias for action Preferred skills: Experience with ERP and Financial Planning tools Experience using Python to parse, structure, and transform data Experience working with CI/CD pipelines Experience leading or working within a scrum, sprint, or other agile framework Past experience supporting product or product finance stakeholders Experience working with cost attribution models for SaaS products and tying products out to CSP cost reports Familiarity with cloud cost management and understanding of cost structures in cloud environments (e.g. FOCUS Framework) Demonstrated experience in cloud computing platforms (e.g., AWS, Azure, Google Cloud) Snowflake is growing fast, and were scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact Snowflake is growing fast, and were scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and .
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.