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Data Engineer (Offshore) Role Overview We are looking for a strong, hands-on Data Engineer to drive technical execution across core data projects. In this role, you will work independently to architect, transform, and analyze complex datasets using Python, PySpark, and Databricks. You will be responsible for maintaining and delivering regular enhancements to our data pipelines, integrating digital analytics data, and ensuring reliable data delivery across the organization. Key Qualifications Technical Proficiency: Strong, hands-on expertise in Python and PySpark for scalable data processing, transformation, and analysis. Platform Experience: Solid hands-on experience with Databricks for pipeline development, optimization, and workspace management. Domain Exposure: Familiarity or prior experience working with Google Analytics (GA4) web/app tracking data. API Development (Plus): Experience building RESTful microservices and data access APIs using FastAPI is a strong advantage. Soft Skills & Work Style: Highly independent self-starter with excellent problem-solving ability and fluent English communication skills to collaborate effectively with global team members and business stakeholders. Key Responsibilities 1. Data Pipeline & Platform Engineering Design, build, and optimize scalable ETL/ELT pipelines using PySpark on the Databricks platform. Perform complex data transformations, data cleaning, and data modeling to support analytical and reporting needs. Ingest and process web/app tracking datasets, including Google Analytics integration pipelines. 2. System Maintenance & Regular Enhancements Maintain existing data pipelines, perform regular performance tuning, and execute continuous feature enhancements. Troubleshoot complex data errors, reduce latency, and ensure strict data quality across systems. 3. API & Data Access Delivery (Optional / Plus) Build and maintain high-performance APIs using FastAPI to expose structured data to downstream applications and services. Core Competencies & Stack Programming & Processing: Python, PySpark, SQL Data Platform: Databricks Analytics Data: Google Analytics (GA4) / Digital Analytics API Frameworks: FastAPI (Nice-to-have) Delivery: Pipeline Optimization, Data Transformation, Performance Tuning
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.