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Job Description We are seeking a talented and driven Data Engineer with expertise in Databricks to join our team in USA. The ideal candidate is passionate about building data platforms, designing scalable solutions, and working in modern cloud-native environments. As a Data Engineer at Eucloid, you will play a key role in developing and optimizing robust data architectures using Databricks Lakehouse Platform, while collaborating with cross-functional teams to drive impactful analytics and machine learning outcomes for our clients. Responsibilities • Serve as the primary technical lead and trusted advisor for the client's Databricks platform, data engineering initiatives, and enterprise reporting ecosystem. • Partner with business and technology stakeholders to define data platform strategy, architecture roadmap, and scalable analytics solutions aligned with business goals. • Design, develop, and oversee implementation of high-performance ETL/ELT pipelines, Lakehouse architectures, and data products using Databricks, PySpark, SQL, and cloud native technologies. • Drive platform reliability, scalability, security, governance, data quality, and cost optimization through engineering best practices and architectural oversight. • Lead and mentor data engineering teams, establish development standards, conduct design reviews, and promote a culture of engineering excellence. • Collaborate with business users, analysts, reporting teams, and data scientists to deliver reliable, production-ready data and reporting solutions. Background & Skills • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative discipline. • 8+ years of experience in Data Engineering, Data Warehousing, and Cloud Data Platforms. • 4+ years of hands-on experience designing and implementing solutions on Databricks. • Strong expertise in Databricks, PySpark, Spark SQL, Delta Lake, Unity Catalog, and Lakehouse architecture. • Proven experience building and managing large-scale data platforms on AWS, Azure, or GCP. • Proficiency in Python, PySpark, SQL, and data modeling for enterprise-scale data solutions. • Hands-on experience with Airflow, dbt, Terraform, Kafka, Databricks Workflows, and Delta Live Tables. • Strong stakeholder management, communication, and team leadership skills; Databricks and/or Cloud certifications are preferred.
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.