Amazon.com Services LLC

Business Intelligence, Data Engineering, operations

DataEngineerI,OTS-DataANCHORTeam

$100–160k Austin, Texas, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Engineer I, OTS - Data ANCHOR Team at Amazon.com Services LLC. Skills: Data engineering, ETL/ELT pipelines, Big data infrastructure, AI solutions. Design, build, and maintain production-grade ETL/ELT pipelines and. Contribute to data governance and quality standards across”

What You'll Achieve.

Drive measurable business outcomes; Improve data practices; Enable self-service data access; Implement GenAI solutions

Industry & Context.

Business Intelligence, Data Engineering, operations
Problems you'll solve

Analyzing data; Interpreting data; Extracting value

What They're Looking For.

Must Have

Bachelor's degree or above in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline, 1+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience, Experience with data modeling, warehousing and building ETL pipelines, Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala), Experience with one or more scripting language (e.g., Python, KornShell)

Nice to Have

Master's degree, Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions, Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools

What You'll Do.

and maintain production-grade ETL/ELT pipelines and

Contribute to data governance and quality standards across

Support implementation automated reporting

Build and maintain semantic layers and dashboard data

Collaborate with Program Managers

Follow and contribute to best practices for data

How You'll Work.

Team & Collaboration

Program Managers; BI teams; Data Engineers; Data Scientists; Operational stakeholders

Full Job Description

Join the OTS Data ANCHOR team to build strategic data infrastructure powering Amazon's Operations Technology ecosystem. Our team provides critical data infrastructure support for OpsTech IT, supporting Amazon's global customer commitment. You'll work at the intersection of large-scale data processing and real-world operational impact — creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, and Amazon Campus. As a Data Engineer, you will collaborate to build and maintain scalable data pipelines and data infrastructure that power AI-driven operational insights and business insights, Science initiatives across Amazon's global fulfillment and maintenance networks. You will build and implement ETL/ELT pipelines, collaborate with Data Scientists, and BIEs to deliver data products that drive measurable business outcomes. You will contribute to AI ready data initiatives and improve our best data practices — including data versioning, pipeline monitoring, and model retraining data support — and help execute against our engineering best practices within the team. You will support day to day business and internal engineering teams by building curated, analysis-ready models and datasets and enabling self-service data access through well-governed data infrastructure. This role directly enables the team's mission to implement GenAI solutions for automated reporting, diagnostics, and predictive and prescriptive analytics across worldwide operations. Key job responsibilities - Design, build, and maintain production-grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence. - Contribute to data governance and quality standards across analytical and ML data products. - Support implementation automated reporting, diagnostic, predictive, and prescriptive analytics. - Build and maintain semantic layers and dashboard data models that power worldwide opera

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