Data & AI Engineer Lead

Req ID: 344686 

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 & AI Engineer Lead to join our team in Remote, Karnātaka (IN-KA), India (IN).

"Job Duties: Role Overview

The Data Quality Architect will lead the design, development, and deployment of a scalable Production Data Quality (DQ) Framework that ensures accuracy, consistency, and compliance across enterprise data pipelines.
This role is responsible for defining the architectural blueprint, rule catalog, and governance model to institutionalize automated and auditable DQ checks across production systems.
The architect will combine deep technical expertise in Python, PySpark, and data governance with the ability to lead framework design, stakeholder alignment, and performance measurement.

Key Responsibilities

Framework Design & Architecture

Architect a metadata-driven, Python/Spark-based framework for automated data validation across high-volume production datasets.

Define DQ rule templates for completeness, integrity, conformity, accuracy, and timeliness.

Establish data quality thresholds, escalation protocols, and exception workflows.

Automation & Integration

Lead the implementation of automated DQ processes integrated with CI/CD and orchestration platforms such as Airflow, Databricks, or Azure Data Factory.

Define parameterized rule execution models for scalability and reuse across multiple data domains.

Governance & Compliance

Align the DQ framework with organizational governance, privacy, and compliance standards (e.g., HIPAA, SOC 2).

Ensure traceability, auditability, and explainability of all DQ rules and outcomes.

Define metadata lineage and rule catalogs in collaboration with governance teams.

Leadership & Collaboration

Partner with engineering and data platform teams to operationalize the framework and integrate into existing pipelines.

Provide technical guidance to data engineers and analysts to ensure consistent adoption and quality delivery.

Present framework outcomes and improvement recommendations to executive leadership.

Monitoring & Continuous Improvement

Develop metrics and dashboards to monitor DQ framework performance and rule effectiveness.

Drive continuous improvement through rule refinement, automation enhancement, and defect prevention analysis.

Minimum Skills Required: | **Category**                 | **Requirement**                                                                                                                                                                                                                                                                                                             |
| ---------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Experience**               | 8–10 years of experience in data architecture, data quality, or data engineering within enterprise data ecosystems.                                                                                                                                                                                                         |
| **Technical Expertise**      | - Expert in **Python** and **PySpark** for large-scale data processing and validation.<br>- Strong command of **SQL** and data profiling methodologies.<br>- Proven experience designing **metadata-driven DQ frameworks** or validation engines.<br>- Familiarity with **orchestration tools** (Airflow, Databricks, ADF). |
| **Governance & Compliance**  | Deep understanding of data lineage, retention, auditability, and compliance (HIPAA, SOC 2).                                                                                                                                                                                                                                 |
| **Platforms & Tools**        | Databricks, Spark, Power BI, Tableau, cloud d"

About NTT DATA

NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com

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 and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.

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