Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer
Dallas, Texas, United States
Open 3 months, first seen by us 93 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
Before you apply
- Employer’s visa record
- 291 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.
What you’ll work on
Full postingDesign and build high-volume batch and real-time data pipelines
Develop event-driven processing with Kafka and Spark
Implement workflow orchestration and scheduling for complex pipelines
Work with cloud data warehouse and cloud-native data platforms
Implement secure secrets, credential, and service authentication practices
From the employer’s posting
Design and develop high-volume batch and real-time data pipelines for enterprise applications and analytics platforms.
Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark.
Implement and manage workflow orchestration and scheduling for complex data pipelines.
Work with cloud data warehouse and cloud-native data platforms to support enterprise-scale workloads.
Implement secure approaches for secrets management, credentials, and service-to-service authentication in production environments.
What you’ll bring
All qualificationsCore experience
- 4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems.
- 4+ years of data or application engineering experience with Java, Python, and SQL.
- 4+ years of experience building and operating real-time or event-driven data systems.
- 4+ years of experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent.
- 4+ years of experience working with cloud data warehouse/data platforms at scale.
- 4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP.
Qualification wording
4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems.
4+ years of data or application engineering experience with Java, Python, and SQL.
4+ years of experience building and operating real-time or event-driven data systems.
4+ years of experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent.
4+ years of experience working with cloud data warehouse/data platforms at scale.
4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP.
Posting record
Report an errorOpen 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.
- Status in our records
- Live
- First seen by us
- Aug 11, 202693 days ago
- Recorded sightings
- 198
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 93
Up longer than most. Similar jobs usually come down between day 6 and day 56.
At Tiger Analytics, jobs usually come down by about day 68.
From 13,338 similar postings that came down, and 27 of Tiger Analytics’s. Coming down is not always a hire.
Tiger Analytics is hiring
74 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is steady
- Its jobs tend to stay up a long time
- 1% of open jobs were reposted
See how this role fits your experience
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.
- Java
- Python
- SQL
- AWS
- Azure
- GCP
- Hadoop
- Kafka
- Spark
- Airflow
Where the posting names them
- Build scalable data processing solutions using distributed computing frameworks such as Spark, EMR, Hadoop, or equivalent technologies. - Develop applications and data solutions using Java, Python, and SQL. - Implement and manage workflow orchestration and scheduling for complex data pipelines.
- 4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems. - 4+ years of data or application engineering experience with Java, Python, and SQL. - 4+ years of experience building and operating real-time or event-driven data systems.
- 4+ years of experience working with cloud data warehouse/data platforms at scale. - 4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP. - 3+ years of experience with workflow orchestration and scheduling tools such as Airflow, Control-M, Autosys, Step Functions, or equivalent.
- Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark. - Build scalable data processing solutions using distributed computing frameworks such as Spark, EMR, Hadoop, or equivalent technologies. - Develop applications and data solutions using Java, Python, and SQL.
- 4+ years of experience building and operating real-time or event-driven data systems. - 4+ years of experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent. - 4+ years of experience working with cloud data warehouse/data platforms at scale.
- Build end-to-end data solutions covering ingestion, transformation, orchestration, streaming, and downstream delivery. - Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark. - Build scalable data processing solutions using distributed computing frameworks such as Spark, EMR, Hadoop, or equivalent technologies.
- 4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP. - 3+ years of experience with workflow orchestration and scheduling tools such as Airflow, Control-M, Autosys, Step Functions, or equivalent. - 2+ years of experience implementing secure secrets and credential management in production environments.
Your next step
Complete your application on apply.workable.com. The employer’s form will show what is required.
Applying through Workable
- No account needed. You can import your resume to fill in the form, or skip that and fill it in yourself.
Already applied? Track this application
Has Tiger Analytics posted this job before?
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.
Demand for Data Engineer roles
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.
About the role
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.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
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.
Job description
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
Tiger Analytics is looking for an experienced Data Engineer to design, build, and operate large-scale batch and real-time data pipelines that power enterprise data and analytics platforms.
You will work closely with Agile engineering, architecture, and product teams to build reliable, scalable data solutions spanning data ingestion, transformation, orchestration, event streaming, and downstream data delivery. The ideal candidate is someone who enjoys solving complex data engineering problems and building highly available systems that operate at enterprise scale.
Key Responsibilities:
- Design and develop high-volume batch and real-time data pipelines for enterprise applications and analytics platforms.
- Build end-to-end data solutions covering ingestion, transformation, orchestration, streaming, and downstream delivery.
- Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark.
- Build scalable data processing solutions using distributed computing frameworks such as Spark, EMR, Hadoop, or equivalent technologies.
- Develop applications and data solutions using Java, Python, and SQL.
- Implement and manage workflow orchestration and scheduling for complex data pipelines.
- Work with cloud data warehouse and cloud-native data platforms to support enterprise-scale workloads.
- Design solutions with a strong focus on reliability, scalability, performance, security, and low latency.
- Implement secure approaches for secrets management, credentials, and service-to-service authentication in production environments.
Requirements
- 4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems.
- 4+ years of data or application engineering experience with Java, Python, and SQL.
- 4+ years of experience building and operating real-time or event-driven data systems.
- 4+ years of experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent.
- 4+ years of experience working with cloud data warehouse/data platforms at scale.
- 4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP.
- 3+ years of experience with workflow orchestration and scheduling tools such as Airflow, Control-M, Autosys, Step Functions, or equivalent.
- 2+ years of experience implementing secure secrets and credential management in production environments.
- 2+ years of experience working in Agile engineering teams.
- Strong understanding of distributed systems, data processing, and enterprise data architecture principles.
- Familiarity with data observability, including monitoring, alerting, SLA management, pipeline health, and data quality.
- Strong problem-solving, communication, and collaboration skills.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Dallas, Texas, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.