{"id":959080,"url":"https://alion.io/job/the-vanguard-group-dataai-engineer-databricks-aws-python-ai","title":"Data/AI Engineer (Databricks, AWS, Python, AI))","company":{"id":253,"name":"The Vanguard Group","domain":"vanguard.com","url":"https://alion.io/company/vanguard","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":75,"open_postings":73,"ghost_share":0.123,"stale_share":0.575,"repost_share":0.205,"time_to_fill_p50_days":28,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Agile","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Context Engineering","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"IAM","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-16T08:12:56Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-11-04T05:28:05Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":2,"flags":["repost"],"days_open":48},"description":"About Vanguard\nFounded 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.\nVanguard India\nVanguard’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.\nRole Summary\nThe Data/AI Engineer is responsible for designing, developing, enhancing, and supporting scalable cloud-based data pipelines, data products, and data-driven applications. This is a hands-on engineering role requiring strong technical expertise in modern data engineering technologies, problem-solving abilities, and a product mindset to deliver reliable, secure, and high-quality data solutions.\nThe role requires the ability to work independently on assigned initiatives while collaborating closely with Technical Leads, Product Owners, Architects, Analysts, and other Engineering teams. The individual will contribute to the design, development, deployment, enhancement, and operational support of modern data platforms and data products that enable business outcomes and data-driven decision making.\nIn addition to delivering new capabilities, the Data/AI Engineer will be responsible for supporting existing data products and applications, performing production support activities, troubleshooting incidents, implementing enhancements, and driving continuous improvement. The individual is expected to take ownership of assigned deliverables from development through production support while seeking guidance from the Technical Lead for complex technical, architectural, or cross-functional decisions.\nResponsibilities\nBuild and optimize data ingestion, transformation, integration, and storage solutions supporting analytical and operational workloads.\nDesign, develop, test, and maintain scalable batch and real-time data pipelines, data products, and cloud-based data solutions.\nOwn assigned deliverables from design through deployment, ensuring quality, reliability, performance, security, and maintainability.\nCollaborate with Technical Leads, Product Owners, Architects, Analysts, and Engineering teams to translate business requirements into technical solutions.\nImplement data quality controls, monitoring, observability, automation, and CI/CD practices to improve platform reliability and engineering productivity.\nSupport and enhance business-critical data products, applications, and platforms through defect resolution, performance improvements, and continuous modernization initiatives.\nTroubleshoot production issues, perform root-cause analysis, implement preventive actions, and contribute to operational excellence.\nParticipate in application-support activities, release support, and production operations, including flexible working hours when required to support critical deliverables, production incidents, business commitments, or global stakeholders.\nContribute to technical documentation, reusable components, engineering standards, and AI-assisted development practices that improve quality and delivery efficiency.\nProactively identify risks, dependencies, and improvement opportunities while working independently with guidance from the Technical Lead when required.\nQualifications and Skills\nBachelor's degree in Computer Science, Information Technology, Engineering, Computer Applications, or a related discipline from a recognized institution.\nMinimum of 5 years of relevant experience with the majority of experience focused on Data Engineering.\nHands-on experience designing, developing, and supporting scalable data pipelines, ETL/ELT frameworks, and cloud-based data solutions.\nExperience delivering data engineering solutions in cloud environments and Agile product teams.\nDemonstrated ability to independently deliver assigned workstreams while collaborating effectively with Technical Leads and Architects.\nExperience supporting production data platforms, data products, and business-critical applications.\nStrong understanding of software development lifecycle, production support, operational excellence, and continuous improvement practices.\nMust have Skills\nCloud Platforms- Hands-on experience with AWS data services such as S3, Glue, Lambda, Redshift, Athena, Step Functions, SNS/SQS, IAM, CloudWatch, and Kinesis, as relevant to the assigned solutions.\nData Engineering - Strong experience with scalable ETL/ELT pipelines, data integration, batch processing, data transformation, and modern data-platform patterns.\nProgramming - Strong hands-on proficiency in Python, PySpark, Pandas, and Advanced SQL, including writing maintainable code and optimizing data-processing workloads.\nData Platforms - Working experience with Redshift, Databricks, and Spark, including incremental processing, data quality, and performance optimization.\nOrchestration and Streaming - Practical experience with Airflow and Kafka, including scheduling, retries, dependency handling, monitoring, and failure recovery.\nDevOps and Infrastructure - Working knowledge of Docker, Terraform, GitHub Actions, Code Pipeline, ECS, ECR, and CI/CD practices.\nAnalytics and Integration - Experience integrating data through REST APIs and supporting datasets consumed by analytics and visualization solutions such as Power BI\nEngineering Practices - Strong understanding of Git, code reviews, automated testing, observability, data quality, security, governance, and production-support practices.\n Core GenAI - Hands on / Familiarity with Prompt & context engineering, RAG, agentic workflows, tool/function calling, structured outputs (Bedrock, LangChain/LangGraph, MCP)\n AWS AI/ML Platform - Hands on / Familiarity of Bedrock (Knowledge Bases, Guardrails, Agents), SageMaker, Lambda, S3, OpenSearch Serverless vectors, Step Functions, IaC (CDK/CloudFormation)\nLocation\nThis role is based in Hyderabad, Telangana at Vanguard India. Only qualified external applicants will be considered.\nOur mission\nVanguard 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.\nOur commitment to you\nVanguard 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:\nFinancial wellness\nWe're committed to enabling your financial success and provide competitive offers and programs.\nPhysical wellness\nWe're committed to providing benefits that support your physical health and wellness.\nPersonal wellness\nWe're committed to providing resources that help support the full scope of your life.\nHow we work\nVanguard 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. 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