Firehose

Firehose Data Jobs

17 jobs found

13d ago

Data Engineer II, IAM and Abuse Prevention

Amazon.com Services LLC Seattle, WA

Seattle, WA

13d ago

$132k - $179k/yr Full time Abuse Prevention Ai Ml Amazon Emr

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Job Description

Data Engineer II, IAM and Abuse Prevention at Amazon builds scalable data pipelines and ML-ready datasets to power security investigations and abuse prevention across Amazon.

Responsibilities

Design, implement, and maintain scalable ETL/ELT pipelines to ingest and transform security telemetry, authorization logs, compliance data, and operational metrics from diverse Amazon sources.
Develop and optimize data models that enable security engineers and scientists to efficiently query and analyze abuse patterns across billions of events.
Create ML-ready datasets for data science and applied science teams.
Own monitoring, alerting, and observability for all data pipelines and solutions, proactively addressing data quality issues.
Review and modernize existing data infrastructure, proposing architectural improvements to boost reliability, reduce costs, and enhance performance.
Design and build new data capabilities from the ground up to support product launches and investigation team needs.
Partner with security engineers, scientists, and investigators to understand data requirements and deliver solutions that accelerate abuse detection and response.
Collaborate with data scientists and applied scientists to support AI and AI-agent centric solutions, ensuring data engineering underpins model training and inference.
Utilize GenAI and ML tools to improve workflows, automate pipeline operations, and strengthen data quality processes.
Develop a deep understanding of partner teams and capabilities, identifying opportunities to ingest new signals and provide intelligence data to downstream consumers.

Requirements

3+ years of data engineering experience.
1+ year of developing and operating large-scale BI data structures for analytics using ETL/ELT processes.
1+ year of developing and operating large-scale BI data structures for analytics using OLAP technologies.
1+ year of developing and operating large-scale BI data structures for analytics using data modeling.
1+ year of developing and operating large-scale BI data structures for analytics using SQL.
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.

Technologies

Redshift
S3
AWS Glue
EMR
Kinesis
FireHose
Lambda
IAM
Hadoop
Spark
SQL

Benefits

Health insurance
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)
Adoption and surrogacy reimbursement coverage
Flexible Spending Accounts
Employee Assistance Program (EAP)
Mental health support
Medical Advice Line

About the Team

The ISAP SafeGuard team blends long term, high impact work with near term innovative solutions to prevent abuse across Amazon.
We value Bias for Action, Dive Deep, Invent and Simplify, and Customer Trust in daily work.
We embrace new approaches, technologies, and innovation while ensuring our solutions are scalable, accurate, and drive action.
We work with some of the most sensitive data at Amazon, which requires careful engineering, strict access controls, and a strong sense of responsibility.

Diverse Experiences

Amazon Security welcomes diverse backgrounds. If you do not meet every listed qualification, we encourage you to apply. Nontraditional paths or early career stages should not deter your candidacy.

Why Amazon Security

Security is central to maintaining customer trust and delivering exceptional experiences. The organization sets a high standard for security across Amazon’s products and services.
Opportunities to grow across areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.

Inclusive Team Culture

A culture of learning and curiosity, with ongoing DEI events and programs to celebrate diverse ideas, perspectives, and voices.

Training & Career Growth

Continuous performance development with knowledge sharing and career-advancing resources to broaden expertise.

Work/Life Balance

Flexible work hours and arrangements designed to support work life harmony.

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13d ago

Data Engineer

Amazon.com Services LLC Bellevue, WA

Bellevue, WA

13d ago

$132k - $206k/yr Full time Python Amazon Emr Amazon Web Services

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Job Description

Onsite Data Engineer role in Bellevue, WA, joining Amazon's PXT Central Science team to build scalable data pipelines, feature extraction, and production-ready analytics.

Responsibilities

Data Pipeline Development: design and maintain scalable data pipelines using native AWS services (Glue, EMR, Lambda); implement monitoring and error handling for data workflows; optimize for performance, reliability, and cost efficiency
Model Productionization and API Development: build and maintain APIs and data serving layers that productionize science models for downstream use; create batch and real-time inference pipelines
Data Integration and Quality: develop scalable feature extraction and processing frameworks for diverse data types; implement robust data quality and validation checks; design flexible schemas to support evolving requirements
Cross-team Collaboration: partner with economics, data science, and software engineering teams to translate analytical requirements into production-ready solutions; participate in technical design reviews and architecture discussions
Analytics and Infrastructure: maintain layered data systems used by economists and scientists; build automated reporting solutions; work across multiple interconnected AWS accounts with security best practices

Requirements

Proficiency in professional software engineering practices across the full software development lifecycle, including coding standards, architectures, code reviews, source control, CI/CD, testing, and operational excellence
3+ years of data engineering experience
Experience with at least one modern programming language such as Python, Java, Scala, or NodeJS
Experience with data modeling, data warehousing, and building ETL pipelines
Experience with AWS technologies including Redshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions
Experience with non-relational databases or data stores (object storage, document or key-value stores, graph databases, column-family databases)
Bachelor's degree or foreign equivalent in computer science, engineering, mathematics, or related field

Technologies

Python
Java
Scala
NodeJS
AWS Glue
AWS EMR
AWS Lambda
Amazon Redshift
Amazon S3
Amazon Kinesis
Amazon Firehose
IAM
Hadoop
Hive
Spark

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance (medical, dental, vision, prescription; Basic Life and AD&D; option for supplemental life plans; EAP; mental health support; medical advice line; FSAs; adoption and surrogacy reimbursement)
401(k) matching
Paid time off
Parental leave

About the Team

The Central Science Team within Amazon’s People Experience and Technology organization (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements that enhance Amazon and the lives, well-being, and value of work for Amazonians. This interdisciplinary group blends science, engineering, and UX to deliver solutions with measurable impact.

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16d ago

Data Engineer

Amazon.com Services LLC Arlington, VA

Arlington, VA

16d ago

$132k - $206k/yr Full time Python Amazon Emr Amazon Web Services

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Job Description

Amazon's PXT Central Science team is seeking a Data Engineer to design, build, and maintain data pipelines and analytics that reveal the drivers behind shifts in employee sentiment, actions, and business outcomes. This on-site role in Arlington, VA collaborates with economists, data scientists, and software engineers to productionize science models and deliver scalable data solutions that support decision-making across the organization.

Responsibilities

Data pipeline development: Design and maintain scalable data pipelines using native AWS services (Glue, EMR, Lambda); implement monitoring and error handling for data workflows; optimize performance, reliability, and cost efficiency.
Model productionization and API development: Develop and maintain APIs and data serving layers that productionize science models for downstream consumption; build batch and real-time inference pipelines.
Data integration and quality: Build scalable feature extraction and processing frameworks for diverse data types; develop robust data quality and validation checks; create flexible schemas supporting evolving requirements.
Cross-team collaboration: Partner with economics, data science, and software engineering teams to translate analytical requirements into production-ready solutions; participate in technical design reviews and architecture discussions.
Analytics and infrastructure: Maintain layered data systems used by economists and scientists; build automated reporting solutions; operate across multiple interconnected AWS accounts with security best practices.

Requirements

Knowledge of professional software engineering and best practices for the full software development lifecycle, including coding standards, software architectures, code reviews, source control, continuous deployments, testing, and operational excellence.
3+ years of data engineering experience.
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
Experience with data modeling, warehousing, and building ETL pipelines.
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases).
Bachelor's degree or foreign equivalent in computer science, engineering, mathematics or equivalent.

Technologies

Python
Java
Scala
NodeJS
AWS Glue
EMR
Lambda
Redshift
S3
Kinesis
FireHose
IAM
Hadoop
Hive
Spark
Generative AI

Benefits

Health insurance (medical, dental, vision, prescription)
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)
Adoption and Surrogacy Reimbursement coverage
Employee Assistance Program (EAP) and Mental Health Support
Medical Advice Line
Flexible Spending Accounts (FSA)
Basic Life & AD&D insurance
Optional supplemental life plans

About the Team

The Central Science Team within Amazon’s People Experience and Technology organization (PXTCS) brings together economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements that enhance Amazon and the lives, well-being, and value of work for Amazonians. This interdisciplinary group combines the talents of science, engineering, and user experience to develop solutions that measurably advance this goal.

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18d ago

Data Engineer

Amazon.com Services LLC Seattle, WA

Seattle, WA

18d ago

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

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Job Description

Join Amazon.com Services LLC as a Data Engineer II on the Prime Video Product Analytics (PVPA) team. This onsite role in Seattle, WA offers a competitive salary range of USD 132,100 to 178,800 per year, along with a comprehensive benefits package that includes health insurance, 401(k) matching, paid time off, parental leave, sign-on payments, and RSUs.

The role centers on building and maintaining data infrastructure and pipelines that power out-of-app analytics, full-funnel customer journey insights, experimentation, and machine learning use cases for personalization and measurement.

Responsibilities

Build and maintain the data infrastructure that powers Prime Video's out-of-app and full-funnel analytics.
Own critical datasets and pipelines that support analytics, experimentation, and machine learning use cases, enabling smarter targeting, personalization, and measurement.
Design, implement, and maintain scalable and reliable data models and ETL pipelines that span the full customer funnel, including the reporting layer for the out-of-app messaging platform and PV marketing channel infrastructure.
Build and enhance the AI tooling and analytics products to enable self-serve and improved efficiency.
Partner with engineering and dependency teams to define data contracts, ensure upstream data reliability, and proactively manage communication and change coordination for data schema updates.
Collaborate with Business Intelligence Engineers and Data Scientists to deliver clean, structured data for dashboards, reporting, experimentation, full-funnel attribution, and ML use cases.
Monitor pipeline health, resolve job and cluster issues, and improve automation, testing, and observability to increase system resilience.
Champion data engineering best practices across the team including documentation, version control, peer reviews, and operational excellence.

Requirements

3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
Experience with SQL

Technologies

Redshift
Oracle
NoSQL
S3
AWS Glue
EMR
Kinesis
FireHose
Lambda
IAM

Benefits

Health insurance
401(k) matching
Paid time off
Parental leave
Sign-on payments
RSUs (restricted stock units)

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18d ago

Data Engineer, Decision Intelligence Technology

Amazon Web Services, Inc. Bellevue, WA

Bellevue, WA

18d ago

$132k - $179k/yr Full time Amazon Emr Amazon Web Services AWS

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Job Description

Amazon Web Services, Inc. is seeking a Data Engineer to join the AWS Kumo team, where the focus is on designing and refining data architecture, ensuring data quality, and maintaining data availability to enable advanced analytics and better AWS Support outcomes. This onsite role is based in Bellevue, WA and involves close collaboration with data scientists, BI engineers, and business partners to translate data into actionable insights. The position offers a salary range of USD 132,100 to 178,800 per year.

Responsibilities

Design and enhance the existing data architecture, elevate data quality, establish monitoring, and ensure data availability across systems.
Work with data scientists to deploy advanced analytics methods that leverage our data assets for statistical analysis, forecasting, clustering, and machine learning.
Collaborate with business analysts across teams to formulate and test hypotheses aimed at improving the AWS Support business outcomes.
Streamline reporting and analysis workflows and promote self-service analytics to empower customers.
Stay current with advances in big data technologies and lead pilot initiatives to architect data solutions capable of scaling with growing AWS customer experience data.

Requirements

At least three years of hands-on data engineering experience.
Proficiency in data modeling, data warehousing, and constructing ETL pipelines.

Technologies

Redshift
S3
AWS Glue
EMR
Kinesis
FireHose
Lambda
IAM

Benefits

Sign-on payments
Restricted Stock Units (RSUs)
Health insurance (medical, dental, vision, prescription)
Basic Life & AD&D insurance and option for Supplemental life plans
Employee Assistance Program (EAP)
Mental Health Support
Flexible Spending Accounts
401(k) matching
Paid time off
Parental leave
Adoption and Surrogacy Reimbursement coverage

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18d ago

Data Engineer

Amazon Web Services, Inc. Dallas, TX

Dallas, TX

18d ago

$132k - $179k/yr Full time Amazon Emr Amazon Web Services Analytics

Apply Now

Job Description

A data engineering professional at AWS will design and maintain analytical data infrastructure, develop metrics and dashboards, and enable data driven decision making. This onsite role is based in Dallas, TX, with a salary range of USD 132,100 to 178,800 per year.

Responsibilities

Design, implement and support an analytical data infrastructure.
Manage AWS resources including EC2, EMR, S3, Glue, Redshift, and related services.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies.
Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
Collaborate with Data Scientists and Business Intelligence Engineers to recognize and help adopt best practices in reporting and analysis.
Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.

Requirements

Bachelor's degree.
Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets.
3+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience.
Experience providing technical leadership and mentoring other engineers for best practices on data engineering.
Experience building and operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
Experience with data modeling, warehousing and building ETL pipelines.

Technologies

SQL
Redshift
Quicksights
AWS Glue
EMR
S3
EC2
IAM
Kinesis
FireHose
Lambda

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.

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18d ago

Data Engineer, PV Prime Video TV - Tech

Amazon.com Services LLC Seattle, WA

Seattle, WA

18d ago

$132k - $179k/yr Full time Amazon Emr Analytics AWS

Apply Now

Job Description

Data Engineer role in PV Prime Video Tech at Amazon, focused on designing and implementing scalable data infrastructure and pipelines to enable data-driven decision making across Prime Video, leveraging AWS big data technologies to ingest and integrate data from multiple sources.

Responsibilities

Support PV Commerce Analytics in a high-impact capacity, designing scalable data infrastructure within a large, complex data warehouse environment and integrating diverse data sources.
Build and maintain data pipelines using AWS big data tools such as Redshift, EMR/Spark, Andes Data Lake, and native AWS services to ingest data from Video Commerce, Digital Commerce, Prime, and Device Platform teams; provide datasets to 50+ downstream teams for reporting, analytics, ML models, and ad-hoc requests.
Create high-performing, scalable data products that empower data driven decisions across Prime Video.
Design intricate data pipelines and models for subscription, transaction, and device registration datasets.
Deliver scalable data solutions on native AWS infrastructure.
Develop data quality validation frameworks and monitoring to ensure data integrity and timeliness.
Architect and optimize batch and near real-time processing workflows using Spark, Redshift, and Andes.
Implement robust orchestration and monitoring for workflows with complex dependencies.
Collaborate with cross-functional teams to onboard new data sources.

Requirements

3+ years of data engineering experience.
Experience with data modeling, warehousing, and building ETL pipelines.
Proficiency in SQL.

Technologies

Redshift
EMR
Andes Data Lake
Spark
S3
AWS Glue
Kinesis
FireHose
Lambda
IAM roles and permissions
SQL

Benefits

Health insurance including medical, dental, vision, and prescription coverage, Basic Life and AD&D with optional supplemental life plans, EAP, mental health support, Medical Advice Line, Flexible Spending Accounts, and adoption or surrogacy reimbursement coverage.
401(k) with matching.
Paid time off.
Parental leave.
Sign-on payments.
Restricted stock units (RSUs).

About the Team

Primarily based in Seattle with additional presence in New York and London, a data-driven organization focused on Prime Video growth and commerce analytics, spanning business intelligence, data engineering, and product management to support commercial and analytical needs.
Cross-functional team building intelligent systems that integrate content and data to deliver personalized customer experiences across streaming, live events, and emerging formats.