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We are seeking an experienced Data Engineer with strong expertise in Snowflake, Python, Azure Cloud, Spark, SQL, and Kubernetes to design, build, and maintain scalable cloud-based data platforms. The ideal candidate should have hands-on experience developing modern data pipelines, deploying AI/ML models, implementing CI/CD practices, and working with healthcare data. Experience with Databricks is highly preferred. The role involves collaborating with data scientists, analysts, and business stakeholders to deliver high-quality, secure, and scalable data solutions that support advanced analytics and machine learning initiatives. Key Responsibilities - Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL. - Build and optimize enterprise data solutions using Snowflake and Azure cloud services. - Develop and manage big data processing workflows using Apache Spark. - Design and optimize data models for analytics and reporting. - Develop, deploy, and monitor AI/ML models in production environments. - Build and maintain CI/CD pipelines using GitHub Actions. - Orchestrate and schedule data workflows using Apache Airflow. - Deploy and manage containerized data applications using Kubernetes. - Integrate data from multiple structured and unstructured sources. - Optimize Snowflake performance, query execution, and warehouse utilization. - Collaborate with Data Scientists, Data Analysts, and business teams to deliver data-driven solutions. - Ensure data quality, governance, security, and compliance throughout the data lifecycle. - Support production issues, troubleshoot data pipelines, and implement performance improvements. - Work with healthcare datasets while ensuring compliance with data privacy and security standards. Required Skills - 47 years of experience in Data Engineering. - Strong experience with Snowflake. - Proficiency in Python programming. - Hands-on experience with Azure Cloud services. - Strong knowledge of Apache Spark. - Excellent SQL development and query optimization skills. - Experience with Kubernetes for container orchestration. - Experience building CI/CD pipelines using GitHub Actions. - Hands-on experience with Apache Airflow. - Knowledge of data modeling, ETL/ELT development, and data warehousing concepts. - Experience deploying and monitoring AI/ML models. - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities. Preferred Skills - Hands-on experience with Databricks. - Experience with Delta Lake and Spark optimization. - Knowledge of Azure Data Factory (ADF). - Experience with Azure DevOps. - Familiarity with REST APIs and microservices. - Experience with Infrastructure as Code (Terraform/Bicep) is a plus. - Understanding of data governance, security, and compliance frameworks. Domain Experience - Experience working in the Healthcare domain is highly preferred. - Understanding of healthcare data models, interoperability, and compliance standards is an added advantage. Qualifications - Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field. Preferred Candidate Profile - Solid understanding of modern cloud data architectures. - Ability to design scalable and high-performance data platforms. - Experience working in Agile/Scrum environments. - Self-motivated with excellent troubleshooting and problem-solving skills. - Strong stakeholder management and cross-functional collaboration skills. - Passion for building secure, reliable, and data-driven solutions. Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida) .
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.