Amazon

DESCRIPTION

We are seeking an innovative Data Engineer III to lead the design and implementation of our enterprise-wide data architecture supporting AADA High Velocity Transformation (HVT) initiatives. In this role, you will define and architect end-to-end scalable data solutions that power our organization's transformation initiatives and products.

A key area of focus will be designing end-to-end scalable data systems that enable real-time transformation insights across Amazon employees, supporting our vision of democratizing transformation capabilities through an AI-powered platform.

You'll be responsible for consolidating and optimizing our data architecture to create a unified view of the transformation landscape, working towards a long term goal of integrating diverse data sources including HR metrics, business KPIs, employee sentiment, and market trends.

Collaboration will be at the heart of your role. You'll work closely with HVT teams, business stakeholders, and analytics partners to develop and integrate data infrastructure that enables rapid, human-centered organizational transformation, with a focus on tackling complex business problems where the logical data model and end-to-end data flow are not yet defined. This includes partnering with PXT and Amazon-wide Engineering teams and line People Analytics teams to leverage existing data infrastructure and establish new data foundations where needed. Similarly, you'll work in tandem with applied scientists, building robust data pipelines and infrastructure capable of supporting sophisticated ML models. These models will be crucial for predicting transformation needs and measuring change effectiveness across the organization.

We're looking for a candidate who excels at simplifying complex data challenges, demonstrates innovative technical solutions, and brings a leadership style that balances innovation with pragmatic implementation. Your ability to navigate ambiguity, drive technical strategy, and collaborate across diverse teams will be key to success in this role.

Short/Medium-Term focus (0-18 months):

• Enterprise architect and strategy - Enables the "complete view of transformation landscape" by consolidating currently fragmented Redshift clusters OR running 0-1 HVT redshift cluster altogether. The DE will have to access, understand and build the approach + its significance.
• Rapidly prototype and iterate on data architectures to support evolving transformation needs (i.e. recursive modeler - infra for A/B testing for org change etc.)
• Partner with applied scientists to create data foundations for ML features including sentiment analysis and change prediction

Long-Term focus (18+ months):

• Sustainable infrastructure, with a focus on expansion into customer and business data infrastructure integration
• Design and implement real-time data pipelines for predictive analytics and digital twin simulations
• Create integrated data solutions that combine transformation metrics with customer and business data
• Become a Transformation Enabler - via real-time data pipelines or build predictive datasets for transformation challenges and simulation (developmental plans to go beyond building data pipeline)

Key job responsibilities

Enterprise Technical Leadership & Architecture:

• Define and own data architecture at the team level, working to simplify, optimize, and remove bottlenecks
• Lead the consolidation and standardization of data architecture across business units, supporting transformation initiatives
• Lead the design, implementation, and successful delivery of large-scale, critical data solutions
• Develop extensible and scalable solutions that meet both immediate needs and long-term architectural goals
• Drive adoption of data engineering best practices across engineering partners
• Make technical trade-offs between competing short-term and long-term requirements
• Implement data mesh principles to enable distributed but governed data ownership
• Design scalable data platforms that enable predictive analytics, ambient intelligence, and AI/ML workloads

Implementation & Development:

• Rapidly prototype and iterate on data architectures to support evolving transformation needs
• Write high-quality code for critical data pipelines and infrastructure components
• Design and optimize logical data models and end-to-end data flows
• Build reusable components and services that resolve architecture deficiencies
• Ensure solutions meet requirements for security, scalability, and maintainability
• Drive operational excellence in data solution development and deployment

Cross-functional Collaboration:

• Work closely with business analysts, data scientists, and software engineers to understand requirements
• Influence team's technical and business strategy through roadmap contributions
• Build consensus across teams on architectural decisions and implementation approaches
• Partner with measurement partners to identify and solve problems where transformation solutions are bottlenecked by data needs

Data Quality & Governance:

• Design and implement robust data quality frameworks
• Establish data governance practices and ensure compliance
• Create efficient data validation and monitoring solutions (monitoring, redundancies)
• Drive improvements in data discovery and accessibility (optimization, cost balancing)

About the team

The High Velocity Transformation team diagnoses, designs for, and delivers innovative change management and organization development solutions to drive positive transformations across the business. Our mission is to create human-centered transformation experiences that position Amazon employees to do the best work of their lives, while raising the bar on delivering for customers.

We are a team of transformation strategists, program leaders, systems and experience designers, and science and analytics experts ready to tackle a broad array of problems at the intersection of business and employee imperatives. We work collaboratively with other groups to drive business impact together.

BASIC QUALIFICATIONS

• 5+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

PREFERRED QUALIFICATIONS

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR and IAM roles and permissions

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $139,100/year in our lowest geographic market up to $240,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.