AWS CDK

AWS CDK Data Jobs

5 jobs found

6d ago

Data Engineer

Amazon.com Services LLC Austin, TX

Austin, TX

6d ago

$126k - $179k/yr Full time Amazon S3 Analytics AWS

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Job Description

Data Engineer at Amazon.com Services LLC onsite in Austin, TX offers the opportunity to build scalable data pipelines and ML ready infrastructure that enable GenAI powered analytics across Amazon's Operations Technology ecosystem. The role provides a competitive salary range and on-site collaboration in a dynamic environment. Salary: USD 125,500 - 178,800 per year. Location: Austin, TX.

Benefits

Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
401(k) Plan

Role overview

The Data Engineer will design, build, and maintain production grade ETL and ELT pipelines alongside big data infrastructure that underpins operational intelligence for the Operations Technology stack. You will create ML ready data pipelines and feature engineering workflows to support Data Science experimentation and production model serving. You will contribute to data governance and quality standards and help implement GenAI driven reporting, diagnostics, predictions, and prescriptive analytics. You will also shape semantic layers and dashboard data models that guide global operations decisions, collaborating with program managers, BI teams, ML engineers, data scientists, and operational stakeholders to align work with OTS goals.

Responsibilities

Design, build, and maintain production grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence.
Develop feature engineering workflows and ML ready data pipelines for experimentation and production model serving.
Contribute to data governance and quality standards across analytical and ML data products.
Support the implementation of GenAI solutions for automated reporting, diagnostics, predictive, and prescriptive analytics.
Build and maintain semantic layers and dashboard data models that power worldwide operations decisions.
Partner with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS goals.
Follow and contribute to best practices for data engineering, including code reviews, testing, monitoring, and documentation.

Requirements

3+ years of data engineering experience
3+ years developing and operating large-scale data structures for business intelligence analytics using data modeling experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions
Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
Bachelor's degree or above in computer science, machine learning, engineering, or related fields, or equivalent experience building and maintaining data flows and pipelines
Proficiency in Python and SQL; experience with PySpark or Apache Spark
Experience with infrastructure as code (CDK, CloudFormation) and CI/CD pipelines for data and ML systems
Experience with data modeling and relational/non-relational database design

Technologies

Redshift
S3
AWS Glue
EMR
Kinesis
FireHose
Lambda
IAM
Python
SQL
PySpark
Apache Spark
CDK
CloudFormation

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6d ago

Data Engineer II, AAE

Amazon Development Center U.S., Inc. Bellevue, WA

Bellevue, WA

6d ago

$132k - $179k/yr Full time Analytics Apache Airflow Artificial Intelligence

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Job Description

Based in Bellevue, WA onsite, this Data Engineer II role focuses on building end-to-end data platforms for AWS AI services and delivering executive insights through automated analytics and revenue reporting.

Responsibilities

Architect and implement complete data platforms for new AWS AI services, establishing schemas, data models, ETL/ELT pipelines, and analytics infrastructure where none exists today
Develop and maintain production ETL/ELT pipelines with AWS Glue, Airflow, Spark, and Python to ingest data from operational, commercial, and telemetry sources into unified data models
Create agentic data workflows featuring automated reporting pipelines that leverage AI/ML to generate business insights, weekly business review summaries, and anomaly detection with minimal manual intervention
Build event-driven data architectures using CDK, Lambda, SNS/SQS, and S3 event notifications to support real-time data ingestion and processing
Develop executive dashboards and self-serve analytics using QuickSight for VP/GM-level leadership across multiple service lines
Ensure revenue data accuracy by implementing and validating revenue attribution models, discount calculations, and financial data pipelines that feed CFO-mandated reporting
Design data models that support both operational analytics (feature adoption, customer health, churn signals) and financial reporting (revenue, billing, forecasting)
Collaborate with Product Management, Finance, Service Engineering, GTM, and Data Science teams to translate business questions into scalable data solutions
Optimize pipeline performance by reducing runtimes, eliminating redundant processing, and improving SLA compliance across production workloads
Mentor engineers, contribute to team standards, and foster a culture of automation, code quality, and operational excellence

Requirements

5+ years of data engineering experience
3+ years of developing and operating large-scale BI data structures for analytics using ETL/ELT processes
3+ years of developing and operating large-scale BI data structures for analytics using data modeling
Experience with data modeling, data warehousing, and building ETL pipelines

Technologies

AWS Glue
Redshift
Athena
QuickSight
Bedrock
SageMaker
CDK
Lambda
SNS
SQS
S3
Airflow
Spark
Python
Kendra
Kiro

Benefits

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, 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
Parental leave
Sign-on payments
Restricted stock units (RSUs)

A day in the life

Design data models for newly launched AWS AI services and deploy ETL pipelines to onboard telemetry and revenue data
Validate data accuracy across financial reporting systems
Architect CDK-based event-driven pipelines and collaborate with Product Managers to define launch metrics
Resolve data discrepancies surfaced by Finance and optimize production queries feeding VP-level weekly business reviews

About the team

The AI Services Data Engineering team builds the data infrastructure behind AWS Armored AI products including Bedrock, AgentCore, QuickSight, Q Business, Kendra, Kiro, and Transform. Our data powers metrics and reporting that inform executive visibility into Agentic AI revenue, adoption, and growth, including automated weekly business reviews with agent-generated summaries and revenue attribution models for multi-billion dollar pricing programs and launch telemetry.

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28d ago

Data Engineer II

Amazon.com Services LLC Bellevue, WA

Bellevue, WA

28d ago

$132k - $179k/yr Full time Analytics Artificial Intelligence AWS

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Job Description

Data Engineer II to build and scale the data infrastructure for Amazon's North American Surface Transportation Linehaul network, designing data pipelines, analytical platforms, and AI powered tools used by operations leaders to monitor performance and drive decisions.

Location

Salary

USD 132,100 - 178,800 per yearly

Responsibilities

Design and maintain scalable data pipelines that ingest and transform operational metrics from sources like Andes, Datanet, and Redshift using SparkSQL, Cradle, and AWS services (Glue, Lambda, S3, Step Functions).
Build and extend AI powered analytical applications using AWS Bedrock, DynamoDB, and Python that generate automated performance summaries and insights.
Own data modeling for new metric onboarding, drive migration of legacy SQL workloads to modern platforms, manage infrastructure-as-code with AWS CDK across gamma and production environments, and implement monitoring, alerting, and validation frameworks to ensure pipeline reliability.
Collaborate with operations leaders and data scientists to translate business needs into data solutions that scale.

Requirements

Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
3+ years of data engineering experience
Minimum experience: 1 year
1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
Experience with data modeling, warehousing and building ETL pipelines

Technologies

Andes
Datanet
Redshift
SparkSQL
Cradle
AWS Glue
AWS Lambda
Amazon S3
AWS Step Functions
AWS Bedrock
DynamoDB
Python
AWS CDK
SQL
EMR
Kinesis
Firehose
IAM (roles and permissions)

Benefits

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
Parental leave
Sign-on payments
Restricted stock units (RSUs)

About the Team

NAST CX Tech sits within Amazon Transportation Services and builds the data and analytics platforms that power operational decision-making for North American Surface Transportation. Our flagship product, Cortex Scribe, is an AI-powered platform that automatically generates performance summaries, deep-dive analyses, and weekly flash reports used by operations leaders across the network. We operate at the intersection of data engineering, applied AI, and operational analytics building tools that t

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28d ago

Data Engineer, Compensation, CPSA

Amazon.com Services LLC Seattle, WA

Seattle, WA

28d ago

$132k - $179k/yr Full time Analytics Apache Airflow AWS

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Job Description

Based onsite in Seattle, WA, the Data Engineer will join the Amazon Compensation Data team to modernize the compensation data warehouse, design scalable data infrastructure, and deliver analytics and automation across business intelligence, data science, and AI workloads using AWS tools.

Responsibilities

Direct the modernization of a global compensation data warehouse used by customers worldwide.
As a data engineer, design scalable data infrastructure solutions and collaborate with business, product, and data science teams to deliver analytics and insights that inform daily decisions across the organization.
Develop end-to-end systems from concept and experimentation through to production deployment.
Design and implement AI agents to automate complex decision processes.
Collaborate with customer teams to identify automation opportunities and assess their impact.
Own the complete project lifecycle including data pipelines, deployment, and monitoring.

Requirements

More than five years of data engineering experience.
Experience in data modeling, data warehousing, and building ETL pipelines.
Proficiency with SQL.
Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, Finance or a related field.
Hands on experience with Python or Scala, developing complex data transformations in Spark, and automating pipelines.
Comfort with AWS services such as EMR (Hive/Spark), Redshift, S3, Glue, and Cloudformation.
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.

Technologies

SageMaker Unified Studio
Redshift
S3
Glue
IAM
Cloudwatch
Apache Airflow
AWS CDK
EMR (Hive/Spark)
Hive
Spark
Python
Scala
Java
NodeJS
SQL
CloudFormation
Kinesis
FireHose
Lambda

Benefits

Health insurance
401(k) matching
Paid time off
Parental leave

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1mo ago

Asset&Wealth Management-Senior Cloud Data Engineer-Vice President

Goldman Sachs Dallas, TX

Dallas, TX

1mo ago

Full time Senior Ai Workflows Analytics

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Job Description

Goldman Sachs' Asset & Wealth Management division is seeking a Senior Cloud Data Engineer at the Vice President level to lead hands-on data pipeline work, containerization on Amazon ECS, and the migration of legacy on‑prem systems to AWS. This role combines practical engineering with architectural guidance to enable scalable data solutions that support wealth management initiatives.

Responsibilities

Active Migration Execution: Directly execute the migration of legacy ETL and microservices to AWS. This includes refactoring monolithic code into containerized services and deploying them to Amazon ECS (Fargate/EC2).
Containerization & Orchestration: Build and maintain Docker images, write complex ECS Task Definitions, and configure service-to-service communication using Amazon ECS Service Connect and AWS Cloud Map.
Data Pipeline Engineering: Develop end-to-end data flows using AWS Glue (PySpark), Amazon EMR, and Snowflake. Implement "Lakehouse" patterns using Apache Iceberg to ensure data portability.
IaC Development: Write and maintain production-grade Terraform or AWS CDK modules to provision VPCs, ECS clusters, and RDS instances. Ensure all infrastructure is version-controlled and deployed via GitHub Actions or GitLab CI.
AI-Augmented Coding: Actively use AI coding assistants (e.g., GitHub Copilot) to refactor legacy SQL, generate unit tests, and automate the creation of boilerplate pipeline code.
Toil Reduction: Identify manual bottlenecks in the migration process and build custom automation tools in Python or Go to streamline data validation and schema conversion.
Code Reviews & Standards: Lead rigorous peer code reviews, enforcing standards for performance, security (IAM least privilege), and maintainability.
Observability Implementation: Hands-on configuration of Amazon CloudWatch Container Insights, and OpenTelemetry to ensure deep visibility into migrated microservices and data jobs.
Performance Tuning: Directly optimize Spark job configurations, Snowflake warehouse sizing, and ECS auto-scaling policies to balance performance.

Requirements

8+ years of hands-on experience in Data Engineering and Cloud Infrastructure, focusing on building and migrating production workloads.
Deep technical expertise in Amazon ECS (Fargate/EC2), including networking (ALB/NLB), task placement strategies, and container security.
Proven experience with modern data platforms such as Snowflake (AI Data Cloud) and cloud-native services, with a good understanding of open-source table formats, specifically Apache Iceberg, to enable interoperability, schema evolution, and high-performance analytics across multiple engines.
Expert-level proficiency in Java, Python and SQL.
Hands-on experience with Spark, Kafka, and orchestration tools like Apache Airflow, Dagster, or dbt.
Deep understanding of data warehousing and modern data lakehouse architecture.
Mentorship: Proven track record of upskilling junior engineers.
Communication: Ability to explain complex technical concepts to non-technical stakeholders in the wealth management business.
Problem Solving: A "builder" mindset with the ability to navigate ambiguity in a fast-paced environment.
Bachelor’s or Master’s degree in computer science, Engineering, Mathematics, or a related field.

Technologies

Amazon ECS (Fargate/EC2)
Docker
AWS Cloud Map
Amazon ECS Service Connect
AWS Glue (PySpark)
Amazon EMR
Snowflake
Apache Iceberg
Terraform
AWS CDK
GitHub Actions
GitLab CI
Java
Python
SQL
Spark
Kafka
Apache Airflow
Dagster
dbt
OpenTelemetry
Amazon CloudWatch Container Insights

Benefits

Health Insurance
Holiday & Vacation Policies
Financial Wellness & Retirement
Health Services
Fitness
Child Care & Family Care
Benefits at Goldman Sachs

Best-in-Class Benefits

Healthcare & Medical Insurance: We offer medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.
Holiday & Vacation Policies: We offer competitive vacation policies based on employee level and office location, with generous vacation entitlements and a minimum of three weeks expected vacation usage each year.
Financial Wellness & Retirement: We assist employees in saving and planning for retirement, offer financial support for higher education, and provide live financial education and content on a variety of topics.
Health Services: We offer medical advocacy, counseling and referral services through EAP, Global Medical, Security and Travel Assistance, Workplace Ergonomics Program, and on-site health centers where available.
Fitness: On-site fitness centers in some offices; reimbursements for fitness club membership or activity up to a pre-approved amount.
Child Care & Family Care: On-site child care centers, back-up care, mother and baby rooms, homework rooms, and resources for expectant parents and returning parents; stipends for adoption, surrogacy, egg donation.

Opportunity Overview

Corporate Title: Vice President
Office Location(s): Dallas
Job Function: Software Engineering
Division: Asset & Wealth Management

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AWS CDK Data Jobs

Data Engineer

Data Engineer II, AAE

Data Engineer II

Data Engineer, Compensation, CPSA

Asset&Wealth Management-Senior Cloud Data Engineer-Vice President

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