Data Engineer, Specialist

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

We are seeking a Data Engineer to design, build and optimise scalable data solutions that power analytics, business intelligence and data-driven decision making across the enterprise. This role will partner closely with data analysts, data scientists, software engineers and business stakeholders to deliver reliable, high-quality data products and modern data platforms.

The ideal candidate combines strong technical expertise in data engineering with the ability to translate business needs into scalable, efficient and maintainable solutions.

Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines for processing large and complex datasets.
• Build, optimize and support data architectures, data models and storage solutions that enable efficient analytics and reporting.
• Integrate data from internal systems, APIs and third-party platforms to create trusted and actionable datasets.
• Develop and maintain solutions for both batch and real-time data processing.
• Ensure data quality, consistency, reliability and availability across enterprise data platforms.
• Collaborate with business stakeholders and technical teams to understand requirements and deliver data-driven solutions.
• Translate business specifications into technical designs, code and scalable data solutions.
• Leverage orchestration and workflow tools such as Apache Airflow or Prefect to automate and manage data pipelines.
• Perform data validation, testing and troubleshooting to ensure accuracy and integrity of data assets.
• Lead all phases of solution development, from design through implementation and production support.
• Conduct code reviews and promote engineering best practices across the team.
• Mentor and develop junior data engineers while contributing to technical standards and continuous improvement initiatives.
• Support platform upgrades, software releases and production deployments.
• Lead and mentor Data and AI Engineers, providing technical direction, coaching, and engineering guidance.
• Lead solution architecture and technical design, ensuring alignment with business objectives, product priorities, and engineering standards.
• Design and optimize scalable data pipelines, cloud data platforms, data models, and storage solutions supporting analytical and operational workloads.
• Architect reliable batch and real-time data processing solutions, incorporating data quality, governance, security, performance, and scalability.
• Partner with Product Owners, business stakeholders, Architects, Analysts, and Engineering teams to translate requirements into sustainable data solutions.
• Take end-to-end technical ownership across design, development, deployment, production reliability, and continuous improvement.
• Evaluate technical options and make informed architecture decisions considering performance, scalability, security, cost, reliability, and maintainability.
• Establish engineering and operational practices covering CI/CD, automation, testing, observability, monitoring, release readiness, and production support.
• Lead complex production incident resolution, root-cause analysis, preventive actions, and reliability improvements, while guiding engineers in troubleshooting and reducing operational risk.
• Drive engineering excellence through architecture/design/code reviews, reusable patterns, DevOps practices, and AI-assisted development.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Computer Applications or a related discipline, or equivalent combination of education and experience.
• Minimum 8 years of experience in data engineering, data analytics, programming, database administration or data management.
• Hands-on experience designing and developing scalable data pipelines, ETL frameworks and data solutions.
• Demonstrated experience in leading technical solutions and guiding engineering teams through design, development, deployment, and production support. 
• Experience working in Agile product environments with strong ownership and accountability.
• Demonstrated experience leading production support for business-critical data platforms, data products, or applications, including major-incident resolution, root-cause analysis, operational readiness, release support, and reliability improvement. 
• Experience defining or improving support models, observability standards, incident-management practices, runbooks, operational metrics, and preventive controls for production data solutions.
• Strong proficiency in SQL and relational database technologies such as PostgreSQL, MySQL, Oracle or SQL Server.
• Strong programming skills in Python, Scala or Java.
• Experience working with large-scale data processing technologies such as Apache Spark, Hadoop or Databricks.
• Experience designing data models, schemas and database solutions that support analytical workloads.
• Proven ability to collaborate effectively across cross-functional teams and communicate technical concepts to business stakeholders.
• Strong product mindset, connecting technical decisions and engineering investments to business and customer outcomes.
• Proven ability to lead, mentor, and influence engineers while remaining technically hands-on.
• Strong analytical, problem-solving, troubleshooting, and technical decision-making skills.
• Effective communication and stakeholder management across technical, business, and product teams.
• Ability to navigate ambiguity, balance competing priorities, and proactively manage risks, dependencies, and trade-offs.
• Strong commitment to engineering excellence, operational reliability, and continuous improvement.
• Willingness to provide technical leadership during critical production incidents, major releases, and business-critical situations outside regular working hours when required.

Preferred Skills and Experience

• Experience working with cloud platforms such as AWS, Azure or Google Cloud Platform.
• Hands-on experience with cloud data technologies including AWS Glue, Redshift, BigQuery or Snowflake.
• Experience with workflow orchestration tools such as Apache Airflow or Prefect.
• Knowledge of data governance, data quality and modern data architecture principles.
• Experience within financial services or other highly regulated industries.
• Deep hands-on experience architecting and delivering AWS-based data solutions using services such as S3, Glue, Lambda, Redshift, Athena, Step Functions, SNS/SQS, IAM, CloudWatch, Kinesis, and EMR. Ability to make architecture decisions covering scale, security, reliability, performance, and cost.
• Advanced experience designing scalable ETL/ELT frameworks, batch and real-time pipelines, reusable engineering patterns, and cloud-native data platforms. Ability to provide technical direction and review complex implementations.
• Advanced proficiency in Python, PySpark, Pandas, and SQL, including code optimization, maintainability, testing, debugging, and establishing development standards for engineering teams.
• Strong architectural and hands-on experience with Redshift, Databricks, dbt, and Spark, including data modeling, incremental processing, workload optimization, performance tuning, and data-quality controls.
• Hands-on experience or strong working knowledge of prompt and context engineering, RAG, agentic workflows, tool/function calling, structured outputs, and responsible AI patterns using technologies such as Amazon Bedrock, LangChain/LangGraph, and MCP. Ability to guide solution design and engineering adoption.
• Hands-on experience or strong working knowledge of Amazon Bedrock, including Knowledge Bases, Guardrails and Agents, along with SageMaker, Lambda, S3, OpenSearch Serverless vector capabilities, Step Functions, and infrastructure as code using CDK or CloudFormation.

Technical Skills

Data Engineering: ETL/ELT, Data Modelling, Data Warehousing, Data Integration, Data Quality

Programming: Python, Scala, Java, SQL

Cloud & Analytics Platforms: AWS, Azure, GCP, Snowflake, Redshift, BigQuery

Big Data Technologies: Apache Spark, Hadoop, Databricks

Databases: PostgreSQL, MySQL, Oracle, SQL Server

Workflow & Automation: Apache Airflow, Prefect, CI/CD

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.