Cloud Architecture

Cloud Architecture Data Jobs

91 jobs found

2d ago

AI Engineer - Lead Software Engineer

JPMorganChase Jersey City, NJ

Jersey City, NJ

2d ago

$152k - $215k/yr Full time Agentic Ai AI Enablement Artificial Intelligence

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Job Description

JPMorganChase invites you to apply for the AI Engineer - Lead Software Engineer role in Jersey City, onsite. The position offers a salary range of USD 152,000 to 215,000 per year. You will lead the architecture and hands-on development of scalable large language model systems and agentic AI platforms for enterprise use, champion cloud-native design on AWS, and establish evaluation and observability standards that elevate reliability, cost efficiency, and developer velocity across teams.

Benefits

comprehensive health care coverage
on-site health and wellness centers
retirement savings plan
backup childcare
tuition reimbursement
mental health support
financial coaching

Responsibilities

Spearhead the architecture and hands-on delivery of scalable agentic AI platforms that serve enterprise workflows
Develop production-grade AI systems featuring agents, capabilities, memory patterns, guardrails, and orchestration of tool usage
Design retrieval and context-engineering strategies such as embeddings, semantic search, grounding, summarization, and management of prompts and versions
Build cloud-native AI services on AWS using containers, serverless patterns, event-driven messaging, and distributed data stores
Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls
Create well-governed APIs and integrations that connect AI capabilities to enterprise platforms, tools, and business processes
Establish evaluation, experimentation, regression testing, and observability frameworks to continuously improve quality and agent behavior
Define engineering standards for reliability, security, and safe AI operation throughout the platform lifecycle
Mentor senior engineers and influence engineering direction through code reviews, architecture discussions, and cross-team technical leadership
Leverage enterprise-approved AI coding assist tools to enhance code quality and delivery speed, validating outputs via peer review, automated tests, and secure coding practices
Share learnings and reusable patterns to boost broader team effectiveness
Apply SDLC toolchain knowledge, including enterprise AI-assisted development and automation capabilities, to maximize the value of automation

Requirements

Formal training or certification in software engineering with at least five years of practical experience
Experience designing and shipping production large language model applications, including agentic workflows and tool integration patterns
Strong software engineering fundamentals and proven ability to deliver cloud-native services on AWS using containers and serverless designs
Proficiency in designing distributed systems with asynchronous workflows, durable messaging, and scalable data access patterns
Experience building retrieval-augmented generation solutions, including embeddings, semantic search, grounding, and prompt lifecycle/versioning
Proven ability to implement evaluation and monitoring for model quality, reliability, and safe behavior over time
Strong API design skills with secure integration patterns and reusable platform capability development
Demonstrated technical leadership, including mentoring, driving architecture decisions, and influencing cross-functional stakeholders
Hands-on experience using enterprise-authorized AI-assisted development tools, with the ability to critically evaluate and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe usage within team practices

Technologies

AWS, Kubernetes, LLM Suite

Federal Deposit Insurance Act

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.

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1mo ago

Data Engineer / Architect III - Finance Domain

Hudson Manpower Cincinnati, OH

Cincinnati, OH

1mo ago Closed

$50 - $55/hr Full time Analytics Business Analytics Business Intelligence

This position is no longer accepting applications (closed Jul 6, 2026).

Job Description

Location: Cincinnati, Ohio (onsite). Compensation: USD 50 - 55 per hour. Employment: W2, full-time on a long-term contract. This Finance domain opportunity from Hudson Manpower pairs hands-on engineering with architectural leadership to drive a large scale M&A data integration program, delivering scalable, governance-driven data platforms that support analytics, reporting, and regulatory compliance.

Benefits

Medical, Dental & Vision Insurance
401(k)
Paid Time Off
Professional Development Opportunities
Additional Benefits Package

Responsibilities

Design and deploy scalable enterprise data architectures to support analytics and operations.
Build and optimize cloud-native ELT/ETL pipelines using Snowflake and DBT.
Develop reusable transformation frameworks and enterprise data models.
Create scalable solutions for analytics, reporting, and operational data needs.
Construct high-performance analytical and operational data structures.
Support data integration initiatives related to mergers and acquisitions.
Analyze and consolidate disparate data sources from acquired organizations.
Standardize data definitions, mappings, and transformation logic across the enterprise.
Ensure accurate migration and reconciliation of financial and operational data.
Support enterprise-wide data consolidation efforts and data governance efforts.
Implement data validation, reconciliation processes, and data lineage practices.
Support governance, auditability, and regulatory reporting requirements.
Improve platform reliability, scalability, and maintainability; assist with disaster recovery planning.
Collaborate with Enterprise Architects, Data Engineers, Business Analysts, Reporting Teams, Data Scientists, and Business Stakeholders.
Translate business requirements into scalable technical solutions and participate in architecture reviews and planning sessions.
Evaluate emerging technologies and engineering best practices to inform roadmaps.

Requirements

Snowflake
DBT
Advanced SQL
Data Warehousing
ELT / ETL Engineering
Enterprise Data Modeling
Data Architecture
Cloud Data Platforms
Data Integration
Data Transformation Frameworks
6+ years of Data Engineering or Data Architecture experience
Strong hands-on Snowflake experience
Advanced SQL development and performance optimization expertise
Experience building DBT transformation frameworks
Strong understanding of Data Warehousing concepts
Experience designing scalable ELT/ETL pipelines
Experience with relational and non-relational databases
Strong knowledge of enterprise data modeling and analytics architecture

Technical Environment

Cloud Data Platform: Snowflake
Data Transformation: DBT; ELT / ETL Frameworks
Databases: Relational and Non-Relational
Analytics & Reporting: SQL; Power BI
Architecture: Enterprise Data Modeling; Data Warehousing; Data Governance
Additional Technologies: Java / J2EE

What success looks like

Deliver scalable and reliable enterprise data solutions that support business needs
Successfully integrate data across merger and acquisition initiatives
Build optimized Snowflake and DBT transformation frameworks
Enhance enterprise reporting, analytics, and governance capabilities
Maintain regulatory-quality data management and strong operational excellence

Ideal Candidate Profile

Highly analytical and detail-oriented with a disciplined approach
Experience in regulated, enterprise environments
Strong hands-on engineering and architectural capabilities
Proven ability to solve complex data integration challenges
Expertise with modern cloud data platforms and transformation tools
Ability to balance technical execution with business aims
Collaborates effectively with technical and non-technical stakeholders

Important Notes

W2 Full-Time Opportunity
Onsite Role – Cincinnati, Ohio
Strong Snowflake Experience Required
DBT & Advanced SQL Expertise Required
Financial Services Experience Preferred
Enterprise Data Architecture & M&A Integration Focus
Submission Deadline: June 2, 2026

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1mo ago

Senior Data Engineer - Financial Transactions & Automation

NVIDIA Santa Clara, CA

Santa Clara, CA

1mo ago Closed

$184k - $288k/yr Full time Senior Azure Databricks Cloud

This position is no longer accepting applications (closed Jul 6, 2026).

Job Description

Join NVIDIA in Santa Clara, California, onsite, as a Senior Data Engineer within the Financial Systems Engineering group. You will help build foundational, scalable data platforms that support NVIDIA’s high performance financial infrastructure and cloud services, enabling automated operations across global finance by integrating diverse systems. The package includes equity and a comprehensive benefits program, with a salary range of USD 184,000 - 287,500 per year.

Responsibilities

Pipeline Architecture & Integrity: design event driven pipelines using Kafka and craft data models that preserve transactional ACID properties for invoices, payments, and adjustments.
Scalable Data Solutions: automate scalable ETL processes and refactor modern data architectures to enhance quality, security, and coverage for rapidly growing business needs.
Operational Excellence: work cross functionally to codify business processes into self measuring systems and troubleshoot complex challenges to maintain reliable financial operations.

Requirements

Bachelor’s degree (or equivalent experience); Master’s preferred.
10+ years of industry experience delivering scalable financial services.
Expertise in building scalable REST APIs backed by PostgreSQL.
Proficiency in Python, Golang, Scala, or NodeJS.
Hands on experience architecting robust ETL/ELT pipelines using Databricks and dbt to manage large scale Delta Lake or Apache Iceberg tables.
Deep understanding of high scale distributed systems, Linux, and cloud infrastructure (AWS/GCP/Azure) using container technologies like Docker and Kubernetes.

Technologies

Kafka
PostgreSQL
Python
Golang
Scala
NodeJS
Databricks
dbt
Delta Lake
Apache Iceberg
Linux
AWS
GCP
Azure
Docker
Kubernetes

Benefits

Equity
Benefits

Ways to Stand Out from the Crowd

Advanced Data Modeling: experience developing data ontology or semantic data layers that map disparate raw data into interconnected objects with defined properties and functions.
Financial Domain Scale: a track record of managing financial or ERP data at internet scale, ensuring transactional integrity and zero data loss.
Modern Operations: an Infrastructure as Code mindset with hands on experience building self healing systems in distributed environments.

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1mo ago

Databricks Data Engineer

Deloitte Tempe, AZ

Tempe, AZ

1mo ago Closed

$87k - $171k/yr Full time Analytics Artificial Intelligence Azure Databricks

This position is no longer accepting applications (closed Jul 6, 2026).

Job Description

Join Deloitte in Tempe, AZ, onsite, as a Databricks Data Engineer. This role supports analytics and AI initiatives through the design, construction, and continual optimization of cloud-based data pipelines. The position offers a salary range of USD 86,700 to 170,900 per year and the opportunity to work closely with both client teams and Deloitte experts to deliver large-scale data transformation programs. You will gain hands-on experience with Databricks, Apache Spark, Python, and SQL while contributing to the modernization of enterprise data platforms and influencing how data supports decision making and innovation.

Responsibilities

Create and sustain data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL.
Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns.
Design and manage batch and streaming data workflows that underpin reporting, analytics, and AI use cases.
Apply data architecture, integration, and modeling practices to improve data quality, scalability, and platform performance.
Collaborate with client teams and Deloitte colleagues to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics.
3+ years of experience in data engineering, ETL development, or data platform engineering.
2+ years building data pipelines in Databricks using Apache Spark, Python, and SQL.
Experience implementing data models, data integration patterns, and cloud-based data processing workflows.
Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.
Ability to travel approximately 50% on average.
Limited immigration sponsorship may be available.

Technologies

Databricks
Apache Spark
Python
SQL
AWS
Azure
GCP
Delta Lake
Databricks Workflows
Unity Catalog
Git

Preferred

Experience with Delta Lake, Databricks Workflows, and Unity Catalog
Experience using Git-based version control and CI/CD pipelines
Experience supporting batch and streaming data workloads
Experience with data warehousing, lakehouse architecture, and performance optimization
Experience supporting analytics or machine learning data pipelines
Experience working in consulting or client service delivery environments

Accommodation

Information for applicants with a need for accommodation: details available here

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1mo ago

Databricks Data Engineer

Deloitte Arlington, VA

Arlington, VA

1mo ago Closed

$87k - $171k/yr Full time Artificial Intelligence Azure Databricks Big Data

This position is no longer accepting applications (closed Jul 6, 2026).

Job Description

Deloitte's Databricks Data Engineer role is based onsite in Arlington, VA, within the Core AI & Data practice. The position centers on designing, building, and optimizing cloud-based data engineering solutions that leverage Databricks to support large-scale transformations, analytics, and AI initiatives. The salary range is USD 86,700 to 170,900 per year.

Responsibilities

Design, build, and sustain data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL.
Support modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns.
Develop and manage batch and streaming data workflows that support reporting, analytics, and AI use cases.
Apply data architecture, integration, and data modeling practices to improve data quality, scalability, and platform performance.
Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs.
Demonstrate the following skills expected for the role:
Ability to work independently and as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
3+ years of experience in data engineering, ETL development, or data platform engineering
2+ years of experience building data pipelines in Databricks using Apache Spark, Python, and SQL
Experience implementing data models, data integration patterns, and cloud-based data processing workflows
Experience working with at least one cloud platform: AWS, Azure, or GCP
Ability to travel 50% on average depending on client engagements
Limited immigration sponsorship may be available

Technologies

Databricks
Apache Spark
Python
SQL
Delta Lake
Databricks Workflows
Unity Catalog
Git-based version control
CI/CD pipelines
AWS
Azure
GCP

Preferred

Experience with Delta Lake, Databricks Workflows, and Unity Catalog
Experience using Git-based version control and CI/CD pipelines
Experience supporting batch and streaming data workloads
Experience with data warehousing, lakehouse architecture, and performance optimization
Experience supporting analytics or machine learning data pipelines
Experience working in consulting or client service delivery environments

Accommodation Information

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applic...

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1mo ago

Lead Data Engineer (Finance Tech)

Capital One Richmond, VA

Richmond, VA

1mo ago Closed

$179k - $205k/yr Full time Big Data Bigdata Cloud Architecture

This position is no longer accepting applications (closed Jul 4, 2026).

Job Description

The Lead Data Engineer role in Capital One's Finance Tech group focuses on designing, building, testing, implementing, and supporting data engineering solutions, delivering cloud-based data platforms via Agile teams to empower financial decision-making.

Responsibilities

Partner with cross-functional Agile teams to design, build, test, deploy, and support technical solutions across full‑stack development tools and technologies
Collaborate with developers who specialize in machine learning, distributed microservices, and full‑stack systems
Work with Java, Scala, and Python, plus open source RDBMS and NoSQL databases, and cloud data warehouses such as Redshift and Snowflake
Share enthusiasm for emerging technologies, experiment with new tools, participate in internal and external tech communities, and mentor other engineers
Collaborate with digital product managers to deliver robust cloud based solutions that enable financial empowerment for millions
Perform unit tests and participate in code reviews to ensure designs are solid, code is clean, and performance is tuned

Requirements

Bachelor’s Degree
Minimum 4 years of experience in application development (internships do not count)
Minimum 2 years of experience with big data technologies
At least 1 year of cloud computing experience (AWS, Microsoft Azure, or Google Cloud)

Technologies

Java
Scala
Python
Redshift
Snowflake
MongoDB
Cassandra
Hadoop
Hive
MapReduce
EMR
Kafka
Spark
Gurobi
MySQL
UNIX/Linux
Shell scripting
AWS
Microsoft Azure
Google Cloud

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation including cash bonuses and long-term incentives

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1mo ago

Data Engineer

Amazon.com Services LLC Austin, TX

Austin, TX

1mo ago Closed

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

This position is no longer accepting applications (closed Jul 3, 2026).

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