NTT DATA Services· enterprise· Oct 5, 2026 · 23d ago
Plano, TX, US
Location
Hybrid
Work mode
Full-time
Schedule
Principal
Level
$170K–$250K est.
Estimated compensation
10+ years exp
Experience
Job description
Req ID: 388323
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 Product Engineer (Databricks) to join our team in Plano, Texas (US-TX), United States (US).
Day to Day Job Duties: (what this person will do on a daily/weekly basis)
Lead the design and implementation of enterprise Data Product standards, architecture patterns, and engineering practices within the Databricks ecosystem.
Partner with business stakeholders, Risk domain teams, Data Product Owners, and technology leadership to identify high-value data products that support critical business use cases and analytics outcomes.
Define and implement reusable data product frameworks, reference architectures, governance controls, metadata standards, and quality requirements to accelerate enterprise adoption.
Architect and build multiple end-to-end MVP Data Products in Databricks, including data ingestion, transformation, quality controls, metadata management, security, lineage, and consumption layers.
Develop scalable data pipelines and Lakehouse solutions utilizing Databricks, Delta Lake, Unity Catalog, Spark, and cloud-native services.
Collaborate with Data Engineers, Data Architects, Governance teams, and platform teams to establish delivery standards that support product-based data management and domain-oriented ownership.
Design and implement data product templates, CI/CD patterns, operational monitoring, observability controls, and automated testing frameworks to support repeatable delivery.
Evaluate existing data assets, business processes, and technology capabilities to identify opportunities for modernization and improved data product adoption.
Create proof-of-value demonstrations and working MVP solutions that validate architecture decisions, demonstrate business value, and establish implementation patterns for future teams.
Lead technical workshops, architecture reviews, and stakeholder discussions focused on data product design, data contracts, interoperability, discoverability, and consumption patterns.
Provide technical leadership and mentorship to engineering teams while driving alignment between strategic business objectives and practical delivery execution.
Support proposal development, solution architecture discussions, effort estimation, and client presentations related to enterprise Data Product and Databricks transformation initiatives.
Basic Qualifications: (what are the skills required to this job with minimum years of experience on each)
Minimum 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, or Enterprise Data Management.
Minimum 5+ years of experience designing and implementing modern cloud-based data platforms and data products.
Minimum 4+ years of hands-on Databricks experience, including Delta Lake, Unity Catalog, Workflows, MLflow, and Lakehouse architecture patterns.
Minimum 5+ years of experience designing scalable data architectures and distributed data processing solutions.
Minimum 4+ years of experience building enterprise data pipelines using Spark, Python, SQL, and cloud-native technologies.
Minimum 3+ years of experience implementing Data Product operating models, Data Mesh concepts, domain-driven data ownership, or product-oriented data delivery approaches.
Minimum 3+ years of experience delivering cloud-based solutions on Azure, AWS, or Google Cloud Platform.
Experience implementing data governance, metadata management, data quality frameworks, lineage, and security controls within modern data platforms.
Experience designing reusable engineering standards, architecture patterns, and platform accelerators that support large-scale enterprise adoption.
Experience engaging directly with business stakeholders to translate business requirements into scalable data product solutions.
Strong communication and consulting skills with the ability to lead architecture workshops, executive discussions, and technical solution reviews.
NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is $116,000-$155,000. 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.
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
Req ID: 388323
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 Product Engineer (Databricks) to join our team in Plano, Texas (US-TX), United States (US).
Day to Day Job Duties: (what this person will do on a daily/weekly basis)
Lead the design and implementation of enterprise Data Product standards, architecture patterns, and engineering practices within the Databricks ecosystem.
Partner with business stakeholders, Risk domain teams, Data Product Owners, and technology leadership to identify high-value data products that support critical business use cases and analytics outcomes.
Define and implement reusable data product frameworks, reference architectures, governance controls, metadata standards, and quality requirements to accelerate enterprise adoption.
Architect and build multiple end-to-end MVP Data Products in Databricks, including data ingestion, transformation, quality controls, metadata management, security, lineage, and consumption layers.
Develop scalable data pipelines and Lakehouse solutions utilizing Databricks, Delta Lake, Unity Catalog, Spark, and cloud-native services.
Collaborate with Data Engineers, Data Architects, Governance teams, and platform teams to establish delivery standards that support product-based data management and domain-oriented ownership.
Design and implement data product templates, CI/CD patterns, operational monitoring, observability controls, and automated testing frameworks to support repeatable delivery.
Evaluate existing data assets, business processes, and technology capabilities to identify opportunities for modernization and improved data product adoption.
Create proof-of-value demonstrations and working MVP solutions that validate architecture decisions, demonstrate business value, and establish implementation patterns for future teams.
Lead technical workshops, architecture reviews, and stakeholder discussions focused on data product design, data contracts, interoperability, discoverability, and consumption patterns.
Provide technical leadership and mentorship to engineering teams while driving alignment between strategic business objectives and practical delivery execution.
Support proposal development, solution architecture discussions, effort estimation, and client presentations related to enterprise Data Product and Databricks transformation initiatives.
Basic Qualifications: (what are the skills required to this job with minimum years of experience on each)
Minimum 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, or Enterprise Data Management.
Minimum 5+ years of experience designing and implementing modern cloud-based data platforms and data products.
Minimum 4+ years of hands-on Databricks experience, including Delta Lake, Unity Catalog, Workflows, MLflow, and Lakehouse architecture patterns.
Minimum 5+ years of experience designing scalable data architectures and distributed data processing solutions.
Minimum 4+ years of experience building enterprise data pipelines using Spark, Python, SQL, and cloud-native technologies.
Minimum 3+ years of experience implementing Data Product operating models, Data Mesh concepts, domain-driven data ownership, or product-oriented data delivery approaches.
Minimum 3+ years of experience delivering cloud-based solutions on Azure, AWS, or Google Cloud Platform.
Nice-to-haves
None flagged.
Application prep
Use the role’s language and application details while tailoring your materials.