Req ID: 316829

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 Manager to join our team in New York City, New York (US-NY), United States (US).

Data Engineer Manager

Ideal candidates for this hybrid model project within NTT DATA’s Data and Artificial Intelligence consulting practice live in the New York City area and are technical management consultants who have very strong communication skills and demonstrated experience engaging with senior business and technology executives in the financial services domain. As a Data Engineering Manager for this onsite project, you will manage an offshore team (of data engineers, data architects and data scientists), as well as ensure successful project execution in this client-facing role.

Key Responsibilities:

1. Help lead the development and articulate long-term strategic goals for data architecture vision and establish data standards for Non-Financial Risk systems and processes.
2. Support the management of NTT DATA’s resources, providing oversight, guidance and SME inputs.
3. Coordinate between Non-Financial Risk business stakeholders and technical teams.
4. Utilize various cloud technologies, including Azure, AWS, GCP, and data platforms like Databricks and Snowflake.
5. Conceptualize and create an end-to-end vision outlining the seamless flow of data through successive stages.
6. Institute processes for governing the identification, collection, and utilization of corporate metadata, ensuring accuracy and validity.
7. Implement methods and procedures for tracking data quality, completeness, redundancy, compliance, and continuous improvement.
8. Evaluate and determine governance, stewardship, and frameworks for effective data management across the enterprise.
9. Develop comprehensive strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup, disaster recovery, business continuity, and archiving.
10. Identify potential areas for policy and procedure enhancements, initiating changes where required for optimal data management.
11. Formulate and maintain data models and establish policies and procedures for functional design.
12. Offer technical recommendations to senior managers and technical staff in the development and implementation of databases and documentation.
13. Stay informed about upgrades and emerging database technologies through continuous research.
14. Collaborate with project managers and business leaders on all projects involving enterprise data.
15. Document the data architecture and environment to ensure a current and accurate understanding of the overall data landscape.
16. Design and implement data solutions tailored to meet customer needs and specific use cases.
17. Provide thought leadership by recommending the most suitable technologies and solutions for various use cases, spanning from the application layer to infrastructure.

Basic Qualifications:

1. 8+ years of hands-on experience across Data Management, Data Engineering, Data Architecture.
2. 5+ years of SQL, Python, and Excel experience.
3. 2+ years of Financial Services experience (industry or FS management consulting).
4. 2+ years of Data Visualization experience (Power BI and/or Tableau).
5. 2+ years of experience managing an offshore team.
6. 2+ years of experience with Cloud-based systems (Azure, AWS, or GCP).
7. 2+ years of Enterprise Data Architecture experience (such as end to data sourcing, pipeline ETL/ELT process, curation, data quality).
8. 2+ years of experience driving end-to-end technology solutions.
9. Ability to travel at least 25%.

Preferred Skills:

1. Possess certifications in AWS, Azure, and GCP to complement extensive hands-on experience.
2. Demonstrated expertise with certifications in Snowflake.
3. Hands-on experience with data science (AI/ML/Gen AI).
4. Hands-on experience with MDM, DQ, DG tools (e.g., Collibra, Informatica, Alteryx, Microsoft Purview, etc.).
5. Experience using R (or similar tools).
6. Valuable "Big 4" Management Consulting experience or exposure to multiple industries.
7. Undergraduate or graduate degree preferred.

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