Amazon Dev Center India
Technology
DataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer at Amazon Dev Center India. Skills: Data engineering, Data modeling, ETL pipelines, SQL. Own end-to-end data pipelines. Design end-to-end data pipelines”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
3+ years of data engineering experience, 4+ years of SQL experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, 2+ years developing large-scale data structures, Experience operating large-scale data structures, Experience with business intelligence analytics, Experience with data modeling, Experience in at least one modern scripting or programming language, Experience with Python, Experience with Java, Experience with Scala, Experience with NodeJS
Nice to Have
Experience with AWS technologies, Experience with Redshift, Experience with S3, Experience with AWS Glue, Experience with EMR, Experience with Kinesis, Experience with FireHose, Experience with Lambda, Experience with IAM roles, Experience with permissions, Experience with non-relational databases, Experience with data stores, Experience with object storage, Experience with document stores, Experience with key-value stores, Experience with graph databases, Experience with column-family databases
What You'll Do.
Own end-to-end data pipelines
Design end-to-end data pipelines
Drive technical design reviews
Author architecture documents
Lead scalability improvements
Lead reliability improvements
Identify infrastructure bottlenecks
Define infrastructure solutions
Execute infrastructure solutions
Build engineering productivity frameworks
Build reusable components
Standardize data patterns
Partner with applied scientists
Define data infrastructure for ML models
Define data infrastructure for forecasting engines
Define data infrastructure for analytics platforms
Define data quality standards
Enforce data quality standards
Translate business requirements
Scope technical solutions
Mentor junior data engineers
Develop junior data engineers
Provide design feedback
Perform pair programming
Operate across multiple concurrent projects
Manage tradeoffs speed
Manage tradeoffs correctness
Manage tradeoffs technical debt
How You'll Work.
Team & Collaboration
Collaborate with product managers; Collaborate with developers; Collaborate with leaders; Partner with applied scientists; Partner with BIEs
Full Job Description
Amazon's Global Procurement Organization manages indirect supply chain for World Wide Operations and Delivery Services. We work with massive amounts of data and leverage them for advanced applications. We are Data Engineers to build the facilities to help enable the Global Procurement Organization to gain deep insights into all facets of indirectly supply management and apply advanced data science for automation and decision making. You are someone who is customer focused, relentless and driven to help us build out a brand-new initiative. You will collaborate closely with product managers, developers and leaders across the org. To be successful in this role, you should have broad skills in database design, be comfortable dealing with large and complex data sets, modeling and designing a strong data warehouse and building self-service data platforms for stakeholders to utilize the data we manage. Key job responsibilities * Own and design end-to-end data pipelines and models for complex procurement domains including spend analytics, supplier risk, contract compliance, and catalog management * Drive technical design reviews and author architecture documents for new data systems and platform components * Lead scalability and reliability improvements — identify bottlenecks in existing infrastructure, define solutions, and execute with or without a team behind you * Build frameworks and reusable components that improve engineering productivity and standardize data patterns across GPT data products * Partner with applied scientists and BIEs to define the data infrastructure needed to power ML models, forecasting engines, and self-service analytics platforms * Define and enforce data quality standards — including data contracts, freshness SLAs, lineage tracking, and observability instrumentation * Translate ambiguous business requirements from procurement operations, finance, and leadership into well-scoped technical solutions * Mentor and develop junior data engineers thro
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