Data Engineer - Data Platform (Spark/Kafka/Flink/Scala/Java)
NTT DATA Services· enterprise· Oct 5, 2026 · 23d ago
Dallas, TX, US
Location
In office
Work mode
Full-time
Schedule
Staff
Level
$157K–$230K est.
Estimated compensation
8+ years exp
Experience
Job description
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a Data Engineer - Data Platform (Spark/Kafka/Flink/Scala/Java) - Onsite Hybrid to join our team in Dallas, Texas (US-TX), United States (US).
Join a team building next-generation, cloud-native data platforms powering real-time and batch data movement at enterprise scale. You will design and develop streaming and batch frameworks, Kafka/Flink/Spark-based processing engines, and cloud-native solutions on Azure and Kubernetes. Ideal candidates have strong distributed systems experience and a passion for platform engineering, automation, and data modernization.
Job Responsibilities Include:
• Design, develop, and support scalable real-time and batch data pipelines using Apache Spark, Apache Flink, Apache Kafka, and Airflow.
• Build and enhance metadata-driven self-service
• data integration platforms and reusable connectors.
• Develop and maintain source and target connectors for relational databases, file systems, Kafka, Cassandra, YugabyteDB, and other enterprise data stores.
• Design, deploy, and operate Kubernetes-based streaming and batch processing platforms.
• Lead cloud migration initiatives from on-premise environments to Microsoft Azure.
• Drive performance tuning, scalability optimization, reliability improvements, and operational excellence across large-scale data workloads.
• Develop cloud-native solutions supporting enterprise data movement and processing.
• Collaborate with product owners, architects, cloud engineering teams, and business stakeholders to deliver enterprise-scale data solutions.
• Contribute to platform modernization, automation, CI/CD implementation, and engineering best practices.
• Support troubleshooting, production stability, and continuous improvement initiatives for critical data platforms.
Basic Qualifications:
• Minimum 8+ years of overall Software Engineering or Data Engineering experience.
• Minimum 5+ years of hands-on experience with Apache Spark for large-scale batch and streaming data processing.
• Minimum 5+ years of hands-on experience with Apache Kafka including event-driven architectures and real-time data streaming solutions.
• Minimum 3+ years of hands-on experience with Apache Flink for stream processing and real-time analytics workloads.
• Minimum 5+ years of experience developing applications using Java and/or Scala .
• Minimum 5+ years of experience writing complex SQL queries and optimizing database performance.
• Minimum 3+ years of experience with Kubernetes and containerized application deployment.
• Minimum 3+ years of experience designing and implementing solutions on Microsoft Azure Cloud .
• Minimum 3+ years of experience building and supporting distributed data platforms using Cassandra, YugabyteDB, PostgreSQL, or similar databases .
• Minimum 3+ years of experience building event-driven architectures and streaming applications.
• Minimum 2+ years of experience implementing CI/CD pipelines , source control, and deployment automation using GitLab, GitHub, or similar tools.
• Minimum 2+ years of experience with cloud-native deployment patterns, containerization, and platform automation.
Travel:
Minimal travel required. Travel may be necessary based on project and stakeholder requirements.
Degree:
Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent work experience.
Preferred Skills:
• Demonstrated experience in performance tuning, troubleshooting, and supporting mission-critical data platforms.
• Experience with Apache Airflow orchestration.
• Experience with metadata-driven data platforms and self-service ingestion frameworks.
• Experience with enterprise cloud migration and modernization programs.
• Experience with platform engineering and internal developer platforms.
• Experience leading technical initiatives, mentoring engineers, or serving as a technical lead.
• Knowledge of DevSecOps, infrastructure as code, and observability frameworks.
NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is $96,492 - $144,738 per annum. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance.
This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.
#L1-NorthAmerica
About NTT DATA
NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.
Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, us.nttdata.com .
NTT DATA endeavors to make us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at us.nttdata.com . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here . If you'd like more information on your EEO rights under the law, please click here . For Pay Transparency information, please click here .
Requirements
Must-haves
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a Data Engineer - Data Platform (Spark/Kafka/Flink/Scala/Java) - Onsite Hybrid to join our team in Dallas, Texas (US-TX), United States (US).
Design, develop, and support scalable real-time and batch data pipelines using Apache Spark, Apache Flink, Apache Kafka, and Airflow.
Build and enhance metadata-driven self-service
data integration platforms and reusable connectors.
Develop and maintain source and target connectors for relational databases, file systems, Kafka, Cassandra, YugabyteDB, and other enterprise data stores.
Design, deploy, and operate Kubernetes-based streaming and batch processing platforms.
Lead cloud migration initiatives from on-premise environments to Microsoft Azure.
Drive performance tuning, scalability optimization, reliability improvements, and operational excellence across large-scale data workloads.
Develop cloud-native solutions supporting enterprise data movement and processing.
Collaborate with product owners, architects, cloud engineering teams, and business stakeholders to deliver enterprise-scale data solutions.
Contribute to platform modernization, automation, CI/CD implementation, and engineering best practices.
Support troubleshooting, production stability, and continuous improvement initiatives for critical data platforms.
Minimum 8+ years of overall Software Engineering or Data Engineering experience.
Minimum 5+ years of hands-on experience with Apache Spark for large-scale batch and streaming data processing.
Minimum 5+ years of hands-on experience with Apache Kafka including event-driven architectures and real-time data streaming solutions.
Nice-to-haves
Demonstrated experience in performance tuning, troubleshooting, and supporting mission-critical data platforms.
Experience with Apache Airflow orchestration.
Experience with metadata-driven data platforms and self-service ingestion frameworks.
Experience with enterprise cloud migration and modernization programs.
Experience with platform engineering and internal developer platforms.
Experience leading technical initiatives, mentoring engineers, or serving as a technical lead.
Knowledge of DevSecOps, infrastructure as code, and observability frameworks.
#L1-NorthAmerica
Application prep
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