Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Dallas, Texas, United States
Live, first seen by us 26 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design, develop, and maintain scalable data pipelines using Databricks, Spark, Python, and Scala
Develop and optimize ETL/ELT processes for ingestion and transformation
Tune and troubleshoot Spark applications for performance and reliability
Schedule and monitor batch jobs and workflow dependencies in Control-M
Resolve job failures and support production deployments and incidents
Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala.
Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability.
Use Control-M to schedule, monitor, and manage batch jobs, workflow dependencies, and data processing pipelines.
Support production deployments, incident resolution, and ongoing maintenance of data engineering solutions.
8+ years of overall Data Engineering experience.
Proficiency in Python and Scala for data processing and application development.
Hands-on experience with Hadoop and big data technologies.
Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
Strong understanding of ETL/ELT processes, data transformations, and distributed data processing.
Experience in performance tuning, debugging, troubleshooting, and production support.
From the employer’s posting.
We help Fortune 500 companies harness the power of Artificial Intelligence, Generative AI, Data Science, Data Engineering and Advanced Analytics to solve their most complex challenges, unlock new growth opportunities, and create lasting business impact.
In the employer’s words · Read in context
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 26
Similar jobs usually come down between day 6 and day 54.
At Tiger Analytics, jobs usually come down by about day 68.
From 11,033 similar postings that came down, and 25 of Tiger Analytics’s. Coming down is not always a hire.
64 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Key Responsibilities: - Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala. - Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
- Strong hands-on experience with Databricks and Apache Spark. - Proficiency in Python and Scala for data processing and application development. - Hands-on experience with Hadoop and big data technologies.
- Experience in performance tuning, debugging, troubleshooting, and production support. - Strong SQL skills and understanding of data management concepts. - Excellent analytical, problem-solving, and collaboration skills.
- 8+ years of overall Data Engineering experience. - Strong hands-on experience with Databricks and Apache Spark. - Proficiency in Python and Scala for data processing and application development.
- Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources. - Work with Hadoop and its ecosystem to process and manage large volumes of structured and unstructured data. - Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability.
- Proficiency in Python and Scala for data processing and application development. - Hands-on experience with Hadoop and big data technologies. - Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
- Work with Hadoop and its ecosystem to process and manage large volumes of structured and unstructured data. - Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability. - Use Control-M to schedule, monitor, and manage batch jobs, workflow dependencies, and data processing pipelines.
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Already applied? Track this application
Yes. We’ve followed 6 other Senior Data Engineer jobs there since May 2026. All 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.
About Tiger Analytics
Shape the Future of AI. Transform the World's Leading Businesses.
Tiger Analytics is one of the fastest-growing AI services firms, partnering with some of the world's largest and most influential organizations to redefine how business gets done. We help Fortune 500 companies harness the power of Artificial Intelligence, Generative AI, Data Science, Data Engineering and Advanced Analytics to solve their most complex challenges, unlock new growth opportunities, and create lasting business impact.
We are at the forefront of the AI revolution, helping enterprises move beyond traditional analytics to embrace Generative AI, agentic AI, intelligent automation, and cloud-native data platforms. A global presence across North America, Latin America, Europe, and India.
At Tiger Analytics, we don't just help businesses adapt to the future—we help them build it.
What you will be doing
We are seeking a Senior Data Engineer to join our advanced analytics and AI team supporting some of our large enterprise clients. In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines, processing large datasets, and managing scheduled data workflows to support enterprise data engineering initiatives.
Key Responsibilities:
Requirements
What we need
Benefits
Why Join Tiger Analytics:
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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Dallas, Texas, United States
Working pattern and location restrictions need checking in the full posting.
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