Work setup in the employer’s posting: HybridFrom the employer’s posting
Design, develop and optimize scalable data pipelines in Python and SQL
Build and manage data models and transformations in DBT
Develop and maintain workflow scheduling in Airflow
Work with Snowflake for warehousing, performance tuning and optimization
Monitor and troubleshoot pipelines to keep delivery on time
Design, develop, and optimize scalable data pipelines using Python and SQL
Build and manage data models and transformations using DBT
Develop and maintain workflows and scheduling using Airflow
Work with Snowflake for data warehousing, performance tuning, and data optimization
Monitor and troubleshoot data pipelines and workflows to ensure timely delivery
4-6 years of experience in data engineering or related field
Strong experience in SQL and data modeling
Hands-on experience with Snowflake (data warehousing, optimization, performance tuning)
Proficiency in Python for data engineering tasks
Experience working with DBT for transformation and data modeling
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
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Day 2
Early. Similar jobs usually come down between day 6 and day 54.
At EXL Service, jobs usually come down by about day 17.
From 11,115 similar postings that came down, and 217 of EXL Service’s. Coming down is not always a hire.
203 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Key Responsibilities - Design, develop, and optimize scalable data pipelines using Python and SQL - Build and manage data models and transformations using DBT
- Strong experience in SQL and data modeling - Proficiency in Python for data engineering tasks - Hands-on experience with Snowflake (data warehousing, optimization, performance tuning)
Required Skills & Qualifications - Strong experience in SQL and data modeling - Proficiency in Python for data engineering tasks
- Good understanding of ETL/ELT processes and data pipeline architecture - Familiarity with cloud platforms (AWS/Azure/GCP) is a plus - Strong problem-solving and analytical skills
- Design, develop, and optimize scalable data pipelines using Python and SQL - Build and manage data models and transformations using DBT - Develop and maintain workflows and scheduling using Airflow
- Hands-on experience with Snowflake (data warehousing, optimization, performance tuning) - Experience working with DBT for transformation and data modeling - Experience with workflow orchestration tools like Airflow
- Develop and maintain workflows and scheduling using Airflow - Work with Snowflake for data warehousing, performance tuning, and data optimization - Ensure data quality, integrity, and reliability across all data systems
- Proficiency in Python for data engineering tasks - Hands-on experience with Snowflake (data warehousing, optimization, performance tuning) - Experience working with DBT for transformation and data modeling
- Experience working with DBT for transformation and data modeling - Experience with workflow orchestration tools like Airflow - Good understanding of ETL/ELT processes and data pipeline architecture
Complete your application on fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.
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Yes. We’ve followed 8 other Senior Data Engineer jobs there since August 2026. 2 came down, usually after about 38 days. 6 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 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.
Key Responsibilities
Required Skills & Qualifications
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