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Vanguard

Manages investment funds and retirement savings

Data Engineer - Specialist

Data EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listed

About the Job

Requirements

  • Minimum 8 years of relevant work experience, including at least 4 years designing and developing scalable data pipelines, ETL frameworks, and database management systems.
  • Bachelor’s degree (B.E./B.Tech) in Computer Science or IT, or a Bachelor’s in Computer Applications (BCA) from a recognized institution.
  • Proficiency in SQL and database technologies such as PostgreSQL, MySQL, Oracle, or SQL Server.
  • Hands-on experience with big data frameworks such as Apache Spark, Hadoop, or Databricks.
  • Strong programming skills in Python, Scala, or Java for data processing and automation.
  • Experience with cloud platforms such as AWS, Azure, or GCP, particularly in data services such as AWS Glue, Redshift, BigQuery, or Snowflake.
  • 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, with ability to make architecture decisions covering scale, security, reliability, performance, and cost.
  • 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.
  • 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.

Responsibilities

  • Develop and maintain efficient ETL pipelines that ingest, process, and transform large datasets from diverse sources.
  • Build and manage data storage solutions using relational and non-relational databases, ensuring high availability, performance, and scalability.
  • Work with APIs, third-party data sources, and internal databases to create unified datasets that provide actionable insights for business stakeholders.
  • Partner with business intelligence analysts, data scientists, and software engineers to design and implement data-driven solutions that meet business requirements.
  • Design optimized data schemas and structures that support analytical workloads and improve query performance.
  • Use orchestration tools such as Apache Airflow or Prefect to automate ETL workflows and improve operational efficiency.
  • Provide technical guidance, review code, and promote best practices within the data engineering team.
  • Lead and mentor Data and AI Engineers by 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 that incorporate 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 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, and code reviews; reusable patterns; DevOps practices; and AI-assisted development.

About the Company

Vanguard

Manages investment funds and retirement savings

Vanguard manages mutual funds, exchange-traded funds, and retirement investments for individuals, financial advisers, and institutions. Its Vanguard 500 Index Fund gives investors exposure to large U.S. companies by tracking the S&P 500, while its lineup also includes actively managed stock and bond funds. Clients invest through brokerage and retirement accounts, workplace plans, or advisers, and advisory services build and maintain portfolios around their goals. Fund expenses and advisory fees pay for investment management and account services, with advisory charges based on the assets managed. Founded in 1975, Vanguard is headquartered in Malvern, Pennsylvania, United States.

Company size
10,001+
Company stage
Debt Financing
Total funding
$4B
Headquarters
Malvern, PA
Founded
1975

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