Noida, Uttar Pradesh, India
Open 3 months, first seen by us 93 days agoWork setup in the employer’s posting: HybridFrom the employer’s posting
Design, build, and maintain scalable AI-ready data pipelines on GCP and Snowflake
Develop and optimize ETL workflows to ingest, transform, validate, and integrate data
Create and curate synthetic datasets reflecting real-world patterns and edge cases
Build APIs and backend workflows for data access and orchestration
Implement monitoring, quality checks, and CI/CD practices
Design, build, and maintain scalable AI-ready data pipelines across GCP, and Snowflake.
Develop and optimize ETL workflows to ingest, transform, validate, and integrate structured data for analytics and AI solutions.
Create and curate synthetic datasets that reflect real-world data patterns, edge cases, and business scenarios for AI model development and testing.
Build APIs and backend workflows to enable seamless data access, integration, and orchestration for AI-driven applications.
Implement monitoring, quality checks, automation, and CI/CD practices to improve reliability, scalability, and operational efficiency.
Open 3 monthsWe first saw this posting 93 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 93
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past EXL Service’s usual: its jobs come down by about day 21.
From 13,630 similar postings that came down, and 281 of EXL Service’s. Coming down is not always a hire.
211 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Strong hands-on experience with ETL pipelines, structured data integration, data modeling, and data quality frameworks. - Proficiency in Python, SQL, and cloud-native services for building scalable and production-ready data systems. - Experience developing APIs, backend services, and workflow orchestration components that support AI and analytics solutions.
As a Cloud AI Data Engineer, you will design, build, and optimize AI-ready data pipelines across GCP, and Snowflake. You will work closely with data science, engineering, and business teams to integrate structured data, create high-quality synthetic datasets, and support scalable AI solutions through robust ETL pipelines, APIs, and backend workflows. This role requires strong hands-on expertise in cloud-native data engineering, performance tuning, cost optimization, and production-grade data systems that enable advanced analytics and AI use cases. - Design, build, and maintain scalable AI-ready data pipelines across GCP, and Snowflake.
As a Cloud AI Data Engineer, you will design, build, and optimize AI-ready data pipelines across GCP, and Snowflake. You will work closely with data science, engineering, and business teams to integrate structured data, create high-quality synthetic datasets, and support scalable AI solutions through robust ETL pipelines, APIs, and backend workflows. This role requires strong hands-on expertise in cloud-native data engineering, performance tuning, cost optimization, and production-grade data systems that enable advanced analytics and AI use cases. - Design, build, and maintain scalable AI-ready data pipelines across GCP, and Snowflake. - Develop and optimize ETL workflows to ingest, transform, validate, and integrate structured data for analytics and AI solutions.
- 3–6 years of hands-on experience in data engineering, ETL development, and cloud-based data platforms. - Strong experience building AI-ready data pipelines across GCP, and Snowflake. - Expertise in designing and generating synthetic datasets that capture real-world patterns, anomalies, and edge cases.
Complete your application on fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
As a Cloud AI Data Engineer, you will design, build, and optimize AI-ready data pipelines across GCP, and Snowflake. You will work closely with data science, engineering, and business teams to integrate structured data, create high-quality synthetic datasets, and support scalable AI solutions through robust ETL pipelines, APIs, and backend workflows. This role requires strong hands-on expertise in cloud-native data engineering, performance tuning, cost optimization, and production-grade data systems that enable advanced analytics and AI use cases.
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Noida, Uttar Pradesh, India
Working pattern and location restrictions need checking in the full posting.
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