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Client: Our client is one of the world's largest investment funds that manages hundreds of billions of dollars. The company's business is focused on several areas: private equity, venture capital, real assets, investment solutions, and global market strategies. Project overview: DataArt specialists work on the project in several areas related to the core business of the client. We are helping to develop a decision support system for investment analysts. The project includes development, optimization, and speeding up applications and databases. Position overview: We are looking for a hands-on Analytics Engineer who can work across both data engineering and analytics/reporting. This is not a Power BI-only role. The ideal candidate should be comfortable owning data tasks end-to-end from understanding source data and building transformation pipelines to creating well-designed datasets and Power BI dashboards. We are looking for someone who is data-first and hands-on. The candidate should be equally comfortable writing SQL/dbt transformations, investigating a data issue, designing an analytics model, and building or modifying a Power BI report. This is a contract position, so we are particularly looking for someone who can ramp up quickly, understand an existing data environment, take ownership of assigned work, and consistently deliver completed solutions. Responsibilities: Build, maintain, and enhance data pipelines and transformation workflows using dbt. Develop clean, reliable, and reusable data models for analytics and reporting. Work with SQL and data warehouse platforms to investigate data, troubleshoot issues, and implement transformations. Develop and maintain Power BI dashboards, reports, semantic models, and DAX measures. Translate business requirements into appropriate data models and reporting solutions. Perform data analysis, validation, reconciliation, and data quality checks. Troubleshoot data issues across the pipeline, from source through transformation to reporting. Take ownership of assigned tasks and independently drive them through development, testing, and completion. Work closely with business, analytics, and engineering teams to deliver production-ready solutions. Requirements: Strong SQL and data analysis skills. Hands-on experience with dbt and modern ELT/data transformation practices. Solid understanding of data modeling, including dimensional modeling, fact/dimension structures, and analytics datasets. Experience working with a modern cloud data warehouse, preferably Snowflake. Strong working experience with Power BI, including data modeling, DAX, dashboard development, and performance considerations. Ability to understand unfamiliar datasets and identify relationships, data quality issues, and transformation requirements. Experience debugging and supporting existing data pipelines and analytics solutions. Comfortable working independently in a fast-paced environment and delivering tasks with limited supervision. .
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.