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At The ReWork Group, we partner with high-growth startups and forward-thinking companies to build the future. As a partner to a leader in geospatial analytics, we are seeking a Senior Data Engineer to architect, enhance, and sustain their primary data infrastructure. In this role, you will be responsible for creating dependable pipelines, overseeing cloud-based data warehouses, and guaranteeing that their machine learning and analytics units have high-availability access to data. This is infrastructure that literally powers global-scale geospatial analytics. We are talking high-throughput data pipelines, cloud-native architecture, and mission-critical uptime for enterprise clients. It's a chance to build platform reliability for a company at the intersection of space tech, AI-driven analytics, and defense! You'll make that real. What You'll Do: Define and evolve the data engineering technology roadmaps aligned to business strategies, enterprise architecture, information security standards. Provide architectural leadership on complex, cross-team data initiatives, ensuring solutions are scalable, secure, resilient, and maintainable. Develop and promote data engineering standards for Lakehouse architecture, ELT/ETL frameworks, data modeling, CI/CD, observability, and governance. Be responsible for technical direction for large or multi-team delivery efforts , ensuring application of modern data engineering and DevSecOps practices. Who You Are: Mastery-level knowledge of the data engineering field and modern data platform technology delivery, with deep experience in one or more key domains such as Lakehouse architecture, distributed data processing, cloud data warehousing, data transformation frameworks, or data governance. Demonstrated ability to build and complete implementation plans for complex, enterprise-scale data platforms and pipelines. Proven experience developing and implementing standards, processes, and operational plans that improve stability, resilience, security, and performance of critical data platforms. Deep expertise with cloud-based data platforms like Azure Data services, Databricks, Snowflake and DBT cloud. Strong proficiency in programming using data processing tools like Azure Data Factory, Fivetran, Databricks notebook, DBT cloud, ETL/ELT frameworks, as well as programming languages such as Python, SQL, Spark (PySpark/Scala) and scripting languages common to cloud data environments.
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.