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Cloud Data Engineer Jobs in Delaware (NOW HIRING)

Agilent

Head of Data Engineering, AI CoE

Wilmington, DE · On-site

$171K - $321K/yr

Solid-line management of AI Data Engineers deployed into pods. * Leads a team responsible for ... cloud estate. * Experience operating data contracts, lineage, and certification models in a ...

Agilent

Data Governance & Quality Engineer

Wilmington, DE · On-site

$124K - $194K/yr

We are seeking an experienced Data Governance & Quality Engineer to play a key role in shaping ... Familiarity with Microsoft Fabric or similar cloud-based analytics ecosystems. * Ability to ...

Agilent

Data Governance & Quality Engineer

Wilmington, DE · On-site +1

$124K - $194K/yr

We are seeking an experienced Data Governance & Quality Engineer to play a key role in shaping ... Familiarity with Microsoft Fabric or similar cloud-based analytics ecosystems. * Ability to ...

Xforia, Inc.

Pyspark Developer

Wilmington, DE · On-site

$51.50 - $66.75/hr

... data stores. Good understanding of cloud technology. Must have strong technical experience in ... Collaborate with the data engineering team to continuously improve data integration pipelines ...

Ampcus Inc

Sr. Software Engineer

Wilmington, DE · On-site

$118K - $156K/yr

... cloud security best practices. • Exposure to machine learning or data engineering frameworks is a plus. Company : Ampcus is a global business, technology consulting and an staff augmentation firm ...

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Cloud Data Engineer information

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How much do cloud data engineer jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for cloud data engineer in Delaware is $62.94, according to ZipRecruiter salary data. Most workers in this role earn between $53.65 and $71.68 per hour, depending on experience, location, and employer.

What are some common challenges a cloud data engineer faces when migrating data to the cloud?

Cloud Data Engineers often encounter challenges such as ensuring data security and compliance during migration, optimizing data pipelines for cloud performance, and managing data integrity across distributed systems. They must work closely with cross-functional teams to minimize downtime and avoid data loss, and frequently address issues related to data format compatibility and legacy system integration. Staying up-to-date with evolving cloud technologies and best practices is also essential for successful data migration projects.

What is the difference between Cloud Data Engineer vs Data Analyst?

AspectCloud Data EngineerData Analyst
Required CredentialsCloud certifications (e.g., AWS, Azure), SQL, programming skillsData analysis certifications, SQL, Excel, visualization tools
Work EnvironmentCloud platforms, big data tools, data pipelinesData visualization, reporting, business insights
Employer & Industry UsageTech companies, finance, healthcare, cloud service providersMarketing, finance, retail, business intelligence

While Cloud Data Engineers focus on building and maintaining cloud-based data infrastructure, Data Analysts interpret data to provide business insights. Both roles require SQL skills, but Cloud Data Engineers emphasize cloud platforms and data pipeline development, whereas Data Analysts focus on data visualization and reporting.

What are the key skills and qualifications needed to thrive as a cloud data engineer?

To excel as a Cloud Data Engineer, you need strong expertise in data modeling, ETL processes, programming languages like Python or SQL, and a solid understanding of cloud platforms such as AWS, Azure, or Google Cloud, often supported by a relevant degree and cloud certifications. Familiarity with tools like Apache Spark, Hadoop, cloud storage systems, and data pipeline orchestration frameworks is typically required. Strong problem-solving skills, attention to detail, and effective communication help you deliver scalable solutions and collaborate with cross-functional teams. These competencies are essential for building robust, secure, and efficient data infrastructure that supports business intelligence and analytics.

What does a cloud data engineer do?

A cloud data engineer designs, builds, and maintains data pipelines and storage solutions in cloud environments such as AWS, Azure, or Google Cloud. They work with big data tools, manage data security, and optimize data workflows to support analytics and business intelligence. Proficiency in programming, database management, and cloud services is essential for this role.

What is a cloud data engineer?

A Cloud Data Engineer is an IT professional who designs, builds, and manages scalable data infrastructure and pipelines in cloud environments. They work with cloud platforms like AWS, Google Cloud, or Azure to create systems that collect, process, store, and analyze large volumes of data. Their responsibilities include setting up data lakes and warehouses, ensuring data quality and security, and enabling data-driven applications. Cloud Data Engineers collaborate with data scientists, analysts, and other stakeholders to support business intelligence and analytics initiatives.
What are popular job titles related to Cloud Data Engineer jobs in Delaware? For Cloud Data Engineer jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Cloud Data Engineer jobs in Delaware look for? The top searched job categories for Cloud Data Engineer jobs in Delaware are:
Cloud Data Engineer jobs near you
Infographic showing various Cloud Data Engineer job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $130,915 per year, or $62.9 per hour.

AWS Lead Software Engineer-Python/PySpark

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Posted 28 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

73rd of 170 rated banks

Job description


We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As an AWS Lead Software Engineer-Python/PySpark at JPMorgan Chase within the Consumer and Community Banking Home Lending team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
  • Design reusable data processing and data quality frameworks, writing production-ready Python/PySpark with testing, performance tuning, and maintainable patterns
  • Build and continuously improve reliable batch and streaming data pipelines, enhancing scalability, security, and operational excellence for critical data systems
  • Develop data models and transformations using SQL and dbt to support analytics, BI, and reporting use cases
  • Create and operate workflow orchestration (e.g., Airflow) to schedule, monitor, and troubleshoot data jobs, leveraging infrastructure-as-code (e.g., Terraform) to provision and manage platform infrastructure
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on experience delivering end-to-end software solutions across system design, application development, testing, and operational stability; proficient in all aspects of the SDLC
  • Advanced programming skills, with strong Python expertise (including unit and integration testing) and advanced PySpark for building and maintaining data processing solutions
  • Proficiency with automation, CI/CD, and continuous delivery practices
  • Hands-on experience building and operating cloud-native solutions on AWS (e.g., EKS/ECS, Lambda, API Gateway, VPC, IAM, S3, RDS/DynamoDB, SQS/SNS, CloudWatch/CloudTrail)
  • Experience building and running cloud data platforms on AWS, Google Cloud, or Azure
  • Experience with large-scale distributed data processing, performance tuning, and optimization
  • Strong SQL/Spark SQL skills, including data modeling, query optimization, and execution plan analysis
  • Experience with modern warehouse/lakehouse ecosystems (e.g., Redshift, BigQuery, Snowflake; Spark/Flink/Trino; Iceberg/Hudi) and using approved AI-assisted development tools with standards to validate correctness, performance, and security
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Preferred qualifications, capabilities, and skills
  • Experience in financial services, ideally supporting home lending products and processes
  • Familiarity with modern front-end technologies and patterns for building user-facing experiences
  • Strong data modeling experience for analytics and reporting use cases
  • Knowledge of data platform security, risk, compliance, and governance practices
  • Experience building delivery automation for data/platform services, including CI/CD and containerized deployments (Docker, Kubernetes)
  • Expertise in modern data/streaming platforms and patterns (Kafka topic design and operations; Spark Structured Streaming and streaming ETL)
  • Ability to coach and mentor teammates, contribute to a collaborative and inclusive culture, and use AI-assisted engineering tools in an enterprise-safe way (spec-driven work, refactoring, code review); plus experience with Delta Lake and how it compares to Iceberg

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

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