Senior Data Engineer
Jersey City, New Jersey, United States
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign and maintain scalable data pipelines using Azure data services, Python, Scala and Spark
Build and manage pipelines in Azure Data Factory, Azure Databricks and Azure Data Lake Storage
Develop and optimize ETL/ELT processes for ingestion and transformation
Optimize Spark applications for performance, scalability and reliability
Monitor pipelines, troubleshoot failures and resolve data processing issues
From the employer’s posting
Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark.
Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
Develop and optimize Spark applications to improve data processing performance, scalability, and reliability.
Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.
- 10+ years of overall Data Engineering experience.
- Proficiency in Python and Scala for data processing and application development.
- Strong experience with Apache Spark and distributed data processing.
- Hands-on experience with Hadoop and big data technologies.
- Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture.
Qualification wording
Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.
10+ years of overall Data Engineering experience.
Proficiency in Python and Scala for data processing and application development.
Strong experience with Apache Spark and distributed data processing.
Hands-on experience with Hadoop and big data technologies.
Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture.
Education & alternatives
What we need - Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field. - 10+ years of overall Data Engineering experience.
Tools in this posting
- Python
- Scala
- SQL
- Azure
- Databricks
- Hadoop
- Spark
Source — Tool mentions in context
What you will be doing We are looking for a Senior Azure Data Engineer with strong expertise in Microsoft Azure data services, Python, Scala, and Apache Spark. The ideal candidate will design, develop, and maintain scalable data pipelines and ETL/ELT solutions to support enterprise data platforms. Key Responsibilities:
Key Responsibilities: - Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark. - Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
- Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. - Proficiency in Python and Scala for data processing and application development. - Strong experience with Apache Spark and distributed data processing.
- Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture. - Strong SQL skills and experience with performance tuning, debugging, troubleshooting, and production support. - Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
- Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources. - Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. - Develop and optimize Spark applications to improve data processing performance, scalability, and reliability.
- 10+ years of overall Data Engineering experience. - Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. - Proficiency in Python and Scala for data processing and application development.
- Develop and optimize Spark applications to improve data processing performance, scalability, and reliability. - Work with Hadoop and related big data technologies where applicable. - Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery.
- Strong experience with Apache Spark and distributed data processing. - Hands-on experience with Hadoop and big data technologies. - Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture.
- Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. - Develop and optimize Spark applications to improve data processing performance, scalability, and reliability. - Work with Hadoop and related big data technologies where applicable.
- Proficiency in Python and Scala for data processing and application development. - Strong experience with Apache Spark and distributed data processing. - Hands-on experience with Hadoop and big data technologies.
Benefits in the posting
Full benefits wording- Why Join Tiger Analytics:
- Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes.
- Benefits: Medical, Dental, Vision, Retirement Accounts, Long and Short Term Disability, Life Insurance, HSA/FSA Accounts (USA) and Discretionary time-off.
From the employer’s posting.
About Tiger Analytics
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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 2026 · 15 days ago
- Recorded sightings
- 23
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on apply.workable.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
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 looking for a Senior Azure Data Engineer with strong expertise in Microsoft Azure data services, Python, Scala, and Apache Spark. The ideal candidate will design, develop, and maintain scalable data pipelines and ETL/ELT solutions to support enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark.
- Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
- Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
- Develop and optimize Spark applications to improve data processing performance, scalability, and reliability.
- Work with Hadoop and related big data technologies where applicable.
- Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery.
- Implement data validation, error handling, and data quality checks to ensure accuracy and consistency.
- Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions.
- Follow coding standards, testing practices, version control, and CI/CD procedures.
- Support production deployments, incident resolution, performance tuning, and ongoing maintenance of data engineering solutions.
Requirements
What we need
- Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.
- 10+ years of overall Data Engineering experience.
- Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
- Proficiency in Python and Scala for data processing and application development.
- Strong experience with Apache Spark and distributed data processing.
- Hands-on experience with Hadoop and big data technologies.
- Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture.
- Strong SQL skills and experience with performance tuning, debugging, troubleshooting, and production support.
- Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
- Familiarity with version control, CI/CD, and deployment practices.
- Excellent analytical, problem-solving, and collaboration skills.
Benefits
Why Join Tiger Analytics:
- Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes.
- Build and Lead at Global Scale: Collaborate with exceptional AI, data, engineering, and consulting talent across geographies to deliver transformative solutions and grow strategic client partnerships.
- Benefits: Medical, Dental, Vision, Retirement Accounts, Long and Short Term Disability, Life Insurance, HSA/FSA Accounts (USA) and Discretionary time-off.
- Continuous Learning & AI Upskilling: Stay ahead of the rapidly evolving AI landscape through continuous learning, hands-on exposure to emerging technologies, and opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms. Grow alongside a team that invests in developing future-ready skills and encourages innovation.
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
Jersey City, New Jersey, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.