Manager, Data Engineering
Vanguard is hiring a Manager, Data Engineering in Hyderabad, India. Level rates it ; you can apply on Vanguard.
Level's read on this job
- Little AI ●○○○ is how Level rates this data engineer role: aI is not part of the work.
- Tools and skills the posting cites include AWS, Azure and Google Cloud.
- Level classifies it as a senior role.
- Level lists 358 other open roles at Vanguard.
- The role was posted within the past two weeks.
AI in this role
Manager of Data Engineering responsible for leading a team to design, develop, and optimize scalable data pipelines and cloud infrastructure.
About Vanguard
Founded in 1975, Vanguard is one of the world's leading investment management companies. The firm offers investments, advice, and retirement services to tens of millions of individual investors around the globe—directly, through workplace plans, and through financial intermediaries.
Vanguard India
Vanguard’s office in India is a significant milestone in our global expansion. We are committed to establishing an enduring technology center in Hyderabad, Telangana and are excited to be adding talent who will focus on Artificial Intelligence (AI), mobile, and cloud-based technologies that drive our business outcomes and deliver a world-class experience for our clients.
Role Summary
The Manager, Data Engineering is responsible for leading a team of data engineers to design, develop, and optimize scalable data pipelines and infrastructure. This role focuses on enabling high-performance data workflows, ensuring seamless data integration and driving automation to enhance data accessibility.
Responsibilites
- Hire, mentor and manage a team of data engineers, fostering a culture of innovation, collaboration and continuous learning in data engineering best practices.
- Design, develop and maintain scalable ETL (Extract, Transform, Load) pipelines to efficiently process and integrate structured and unstructured data from multiple sources.
- Build and maintain scalable, fault-tolerant data architectures, ensuring efficient data storage, retrieval and processing across cloud and on-premises environments.
- Oversee the design, implementation and performance tuning of relational and NoSQL databases, ensuring data consistency, security and accessibility.
- Automate data ingestion, transformation and validation processes to enhance data pipeline efficiency and reduce manual intervention.
- Develop cloud-based data solutions using platforms like AWS, Azure, or Google Cloud, leveraging technologies such as Spark, Hadoop and Kafka for large-scale data processing.
- Work closely with data scientists, analysts and business intelligence teams to understand data requirements and develop scalable solutions for analytics and reporting.
- Proactively monitor data pipelines and systems for performance issues, troubleshoot failures and implement preventive measures for system reliability.
- Partner with business and IT leaders to align data engineering initiatives with company goals, ensuring seamless integration of data-driven solutions across departments.
- Lead, coach, and develop high-performing data and technology teams, including hiring, performance management, workforce planning, and talent development.
- Drive delivery of strategic initiatives across data engineering, data warehousing, data lakes / lakehouses, data integration, data governance, data quality, analytics, and business intelligence.
- Partner with business, product, architecture, and engineering stakeholders to translate priorities into product roadmaps, delivery plans, and measurable outcomes.
- Lead product-oriented teams with end-to-end accountability for the development, delivery, maintenance, production support, reliability, and continuous improvement of data products.
- Drive Agile practices, including intake management, backlog prioritization, estimation, sprint and release planning, and delivery governance.
- Manage capacity planning, resource forecasting, delivery commitments, risks, issues, and cross-team dependencies to enable predictable execution.
- Leverage AI-enabled tools and capabilities to improve personal and team productivity, automate and streamline day-to-day workflows, and accelerate responsible AI adoption across the team by identifying practical use cases, encouraging experimentation, and embedding effective AI practices into how the team works.
- Ensure data solutions are scalable, secure, reliable, reusable, and compliant with applicable technology, risk, privacy, and information security standards.
- Promote effective data governance, data quality, metadata management, lineage, ownership, and stewardship practices.
- Monitor delivery, quality, and operational health through relevant metrics, and provide clear, concise updates to stakeholders and leadership.
- Foster strong stakeholder relationships and communicate complex data and technology topics effectively to technical and non-technical audiences.
- Promote automation, standardization, engineering excellence, cost optimization, and modern data practices, including cloud and AI-enabled capabilities.
- Drive a culture of accountability, collaboration, innovation, continuous learning, and business-outcome ownership.
- Provide leadership during major incidents and critical production events, partnering with support and engineering teams to drive timely resolution, stakeholder communication, and service recovery while ensuring operational continuity.
- The Manager, IT Delivery is responsible for leading high-performing data and technology teams and delivering strategic data initiatives that generate measurable business value.This role combines people leadership, product delivery, stakeholder management, and operational oversight. The manager will lead teams operating across data engineering, data platforms, data warehousing, data lakes, data governance, data quality, and analytics.The manager will have end-to-end accountability for the development, delivery, maintenance, production support, reliability, and continuous improvement of data products. The successful candidate will bring strong leadership and communication capabilities, experience managing product-oriented teams, and a sound understanding of modern data ecosystems. The role requires the ability to translate business priorities into executable delivery plans, develop engineering talent, manage delivery commitments, and ensure the scalability, quality, security, and reliability of data solutions.
Qualifications and Skills
- Minimum 8 years of relevant work experience, with at least 5 years in a leadership role managing data engineering teams and large-scale data infrastructure.
- Bachelor’s degree (B.E./B.Tech) in Computer Science, IT, or a related field or Diploma in Data Science/Data Engineering.
- Strong expertise in ETL development, data warehousing and real-time data processing frameworks.
- Hands-on experience with SQL, Python, Spark, Kafka and cloud platforms (AWS, Azure, Google Cloud).
- Proficiency in database technologies (PostgreSQL, MySQL, MongoDB, Snowflake, Big Query) and distributed computing frameworks.
- Proven experience leading teams in a product-based environment with responsibility for delivery execution and stakeholder management.
- Strong understanding of Agile delivery practices, backlog management, sprint planning, and Jira.
- Experience leading data-focused technology initiatives, including data engineering, analytics, data quality, governance, or modern data platforms.
- Strong people leadership, coaching, and talent development skills.
- Excellent stakeholder management, communication, and influencing abilities.
- Demonstrated ability to drive execution, manage ambiguity, solve complex problems, and lead organisational change.
- Ability to understand technical concepts and effectively partner with engineering teams to deliver business outcomes.
- Experience in financial services or other highly regulated industries.
- Exposure to cloud-based data platforms and AI-enabled technology initiatives.
- Agile, Scrum, PMP, SAFe, or related certifications preferred.
- Experience leading cloud data platform, data modernization, or platform transformation initiatives.
Location
This role is based in Hyderabad, Telangana at Vanguard India. Only qualified external applicants will be considered.
Our mission
Vanguard adheres to a simple purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.
Our commitment to you
Vanguard takes the same long-term view of your success—at work and in life—with Benefits and Rewards packages that reflect what you care about, throughout all the phases and stages of your life. Our Total Rewards programs provide you and your loved ones with wellness support for key areas in your life:
Financial wellness
We're committed to enabling your financial success and provide competitive offers and programs.
Physical wellness
We're committed to providing benefits that support your physical health and wellness.
Personal wellness
We're committed to providing resources that help support the full scope of your life.
How we work
Vanguard has implemented a hybrid working model for most of our employees (crew members), designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
How we rate this
Manager, Data Engineering at Vanguard rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where team management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Safety, Data Engineering, ETL, Data Pipelines, and Team Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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