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Senior Data Engineer, Strategic Partnerships & IMPACT360Amazon Web Services (AWS) • Seattle, Washington, United States
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Senior Data Engineer, Strategic Partnerships & IMPACT360

Amazon Web Services (AWS)
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

Amazon Web Services (AWS) is seeking a Senior Data Engineer to join our team. This is a unique opportunity to join a centralized business development team that manages strategic partnerships across all of Amazon. Our team generates, manages, and executes complex and high‑impact partnership deals, managing relationships and negotiations for partnerships that have broader implications to AWS and other Amazon business units. This role will be part of our Strategic Initiatives team where we dive deep and provide thoughtful technical analysis, but are adaptable and action‑oriented, focused on quickly gaining enough context to enable informed decision‑making. AWS Strategic Initiatives is a small, tight‑knit team that values authentic, strong‑willed individuals who think creatively and will proactively seek out opportunities to advance the growth initiatives of Amazon's businesses.
This position is part of the AWS Specialist and Partner Organization (ASP). Specialists own the end‑to‑end go‑to‑market strategy for their respective technology domains, providing the business and technical expertise to help our customers succeed. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together they provide our customers with the expertise and scale needed to build innovative solutions for their most complex challenges.
This is a senior data engineering role on a small, technical team. You will own the data architecture for key domains of an internal deal intelligence platform, the system that unifies what Amazon buys and what it sells into a single decision framework that leaders rely on for portfolio decisions. The platform fuses AWS revenue, vendor spend, contract structures, and competitive dynamics, ingesting data from thousands of buy‑side agreements and dozens of upstream systems, resolving messy real‑world entities into trusted relationships, and powering the analytics, forecasting, and AI layer on top. You'll own the design within your domains and shape the architecture decisions the BI and ML layers above depend on.
You will operate where the business problem is defined but the technical approach is not. As the platform's role grows, a central part of this work is evolving how it sources, models, and serves data: moving toward governed, reusable, directly‑consumed data products, with incremental, retry‑safe, and atomically published datasets. You'll help shape that target architecture and drive the migration within your domains, without disrupting the pipelines finance and leadership depend on daily.
You will onboard and integrate data from teams across Amazon, investigating source‑system behavior, resolving conflicts across inconsistent real‑world data, and driving alignment across organizations that have not shared data before. This work is as much cross‑team investigation and stakeholder management as it is code.
You will design and operate scalable data systems within your domain that serve multiple stakeholders with different access patterns: batch analytics for finance, governed and row‑level‑secured reporting for leadership, and curated datasets for model training. You'll work across the full data‑engineering stack, including distributed data processing, workflow orchestration, an open table‑format lakehouse, a SQL query and serving layer, governed cross‑account data sharing, and BI, on AWS (today, technologies such as Glue/Spark, Airflow, Iceberg, Athena, and Lake Formation, evolving as we modernize). The specific tools matter less than the judgment to choose the right one, simplify complexity, and build systems that are extensible and easy to operate. You will also partner with our science team to build the data infrastructure behind forecasting and reinforcement‑learning initiatives, including feature pipelines, training datasets, decision logs, and reward signals.
Key job responsibilities
Own the data architecture for your domain areas (e.g., ingestion, entity resolution, vendor relationship modeling) and contribute to broader platform architecture decisions
Deliver with limited guidance where logical data models and end‑to‑end data flows are not yet defined
Onboard and integrate disparate data sources from across Amazon (AWS, Retail, Procurement, Finance, vendor systems); resolve conflicts across inconsistent real‑world data and drive cross‑team alignment on data definitions and ownership
Evolve data sourcing and modeling toward governed, reusable, directly‑consumed data products; drive the migration within your domains without disrupting downstream consumers
Build and operate pipelines across distributed processing, orchestration, and an open‑lakehouse foundation on AWS (e.g., Glue/Spark, Airflow, Iceberg, Athena), governed with Lake Formation and cross‑account IAM
Raise operational excellence: incremental and retry‑safe loads, atomic publication, dependency‑aware scheduling, and data‑quality validation
Design data systems within your scope that serve diverse access patterns (batch analytics, governed BI, ML training datasets)
Partner with the science team to build the data infrastructure for forecasting and reinforcement‑learning work, including feature pipelines, training datasets, decision logs, and reward signals
Drive engineering and operational excellence best practices across the data infrastructure
Mentor and develop peers
Make trade‑offs between short‑term delivery needs and long‑term architectural scalability
Basic Qualifications
5+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with distributed data processing using Spark (or equivalent) and workflow orchestration (e.g., Airflow)
Strong SQL skills and proficiency in at least one scripting language (Python preferred) for data manipulation and pipeline development
Experience designing data schemas and operating data stores in support of analytics and downstream consumers
Experience working with cloud data services (AWS preferred)
Preferred Qualifications
Experience with training and deploying machine learning systems to solve large‑scale optimizations, or experience with data infrastructures: relational analytic DBMS, Elastic‑Search, and Big Data EMR/EC2/Glue/Lambda
Experience designing data architecture and end‑to‑end data flows in ambiguous, loosely‑defined problem spaces
Experience with open table formats (Iceberg, Hudi, or Delta Lake) and lakehouse architectures on a cloud object store
Hands‑on experience with the AWS data stack (Glue, Athena, Lake Formation, S3, IAM) and governed cross‑account data sharing
Experience with entity resolution, record linkage, or building unified/"golden" records from inconsistent multi‑source data
Experience partnering with science or ML teams to productionize data for model training and inference
Experience onboarding and integrating data from many disparate source systems, and driving cross‑team alignment on data definitions and ownership
Experience modernizing or re‑architecting legacy data pipelines toward reusable, governed data products
Track record of mentoring engineers and driving operational excellence (data quality, reliability, observability)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually
Company Amazon Web Services, Inc.
Job ID: A10454511
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  • Seattle, Washington, United States

Sprachkenntnisse

  • English
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