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Remote Applied Computer Science Jobs in Delaware

For the right candidate we may consider remote. Experienced full stack software engineer who has a ... Degree in Software Engineering, Computer Science or another related field * 7+ years building ...

R&D Software Security Officer

Wilmington, DE · On-site +1

$143.76K - $240.35K/yr

Perform architectural and design reviews to ensure security-by-design principles are applied ... Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical ...

Endpoint Experience Analyst

Wilmington, DE · On-site +1

$100.79K - $160.26K/yr

... applied to technical solution design and implementation; and understanding of legal industry ... Bachelor's Degree in Information Technology, Computer Science, or related technical discipline.

Product Manager

Dover, DE · On-site +1

$130K - $150K/yr

Product Manager Remote - USA We are looking for an experienced Product Manager passionate about ... Your Qualifications MS/BS degree in Computer Science, Engineering, or equivalent preferred. 3-5 ...

Senior Tax Research Specialist

Dover, DE · Remote

$69K - $69.50K/yr

Undergraduate degree in Accounting, Computer Science, or related field * CPA or master's degree is ... Ability to work extended schedule as required to meet objectives #LI-AM1 #LI-Remote ...

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Remote Applied Computer Science information

What is the difference between Remote Applied Computer Science vs Remote Software Developer?

AspectRemote Applied Computer ScienceRemote Software Developer
Required CredentialsBachelor's in Computer Science or related field; certifications varyBachelor's in Computer Science or related field; certifications optional
Work EnvironmentResearch, data analysis, algorithm development, often in tech or academiaDesign, coding, testing, and maintaining software applications
Employer & Industry UsageTech companies, research institutions, academiaTech firms, startups, software development agencies
Common Search & ComparisonYesYes

Remote Applied Computer Science focuses on research, algorithms, and data analysis, often in academic or research settings. Remote Software Developers primarily design and build software applications. While both roles require a computer science background, their daily tasks and industry applications differ significantly.

What are popular job titles related to Remote Applied Computer Science jobs in Delaware? For Remote Applied Computer Science jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Remote Applied Computer Science jobs in Delaware look for? The top searched job categories for Remote Applied Computer Science jobs in Delaware are:
What cities in Delaware are hiring for Remote Applied Computer Science jobs? Cities in Delaware with the most Remote Applied Computer Science job openings:
Infographic showing various Remote Applied Computer Science job openings in Delaware as of May 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.
Data Solution Architect

Data Solution Architect

Syntricate Technologies

Wilmington, DE • On-site, Remote

$65 - $70/hr

Other

Posted 16 days ago


Job description

Data Solution Architect

Buffalo, NY or Wilmington, DE (3 days onsite/2 days remote), OR Remote w/ travel 6+-month contract to hire Web Cam Interview $65-$70/Hr on W2 (Will be expected to travel to Buffalo, NY and/or Wilmington, DE every 4-6 weeks with Monday through Thursday in office) Travel expense reimbursed by client Proven track record in deploying scalable financial systems (e.g., payment gateways, digital wallets, stablecoin or cryptocurrency systems preferred) (required).

Job Title: Data Solution Architect Location: Buffalo, New York (Preferred) / Remote (Will be expected to travel to Buffalo, NY every 4-6 weeks with Monday through Thursday in office.)

Job Summary

The Data Solution Architect is responsible for designing and delivering enterprise-grade data platforms and solutions that enable advanced analytics and business intelligence. This role requires deep expertise in data engineering, cloud-native architecture, and modern data technologies. The architect will work closely with engineering, product, and compliance teams to build secure, scalable, and regulatory-compliant data solutions. All solutions must align with the principles, standards, and reference architectures established by the Enterprise Architecture function, ensuring consistency, interoperability, and strategic fit across the organization.

Key Responsibilities:
  • Solution Architecture: Architect and deliver cloud-based data platforms (e.g., Azure Data Lake) and scalable data pipelines using technologies such as Databricks, Kafka, etc.
  • ETL/ELT Frameworks: Develop and implement ETL/ELT frameworks for ingesting, transforming, and integrating data from diverse sources, including legacy financial systems, SaaS platforms, and real-time data streams.
  • Data Platform Deployment: Design and oversee deployment of data warehouses, lakehouses, and analytics sandboxes to support business intelligence, machine learning, and reporting needs inclusive of Power BI and Snowflake.
  • Data Governance: Define and enforce data governance, metadata management, and data quality standards in accordance with Enterprise Architecture guidance and regulatory requirements.
  • Enterprise Architecture Collaboration: Collaborate with Enterprise Architecture to ensure all solutions adhere to architectural standards, reference models, and technology roadmaps.
  • Technology Evaluation: Lead technical evaluations and proof-of-concept projects for emerging data technologies (e.g., real-time analytics, data mesh, AI/ML platforms).
  • Technical Documentation: Produce deliverables such as architecture diagrams, data flow maps, security models, and technical documentation for solution handoff and operational support.
  • Agile/DevOps Leadership: Guide Agile/DevOps teams in implementing CI/CD pipelines, automated testing, and infrastructure-as-code for data solutions.
Expected Skills:
  • Data engineering platforms, big data technologies, and cloud-native development (microservices, Kubernetes).
  • API design (REST) and integration tools (ETL/ELT).
  • Stakeholder communication (technical and non-technical audiences).
  • Leadership in Agile/DevOps environments.
  • Analytical problem-solving for complex data systems.
  • Project management: proficiency in tools like Jira; familiarity with SDLC and CI/CD pipelines.
Expected Knowledge:
  • Foundational Understanding: Data modeling, data pipeline orchestration, data quality management, metadata management, and data lifecycle.
  • Data Platforms: Data lakes, warehouses, and lake house architectures; distributed systems and cloud data services.
  • Data Engineering: ETL/ELT processes, real-time and batch data processing, data integration, and automation.
  • Financial Systems: Payment networks, liquidity management, and settlement processes (as relevant to data flows).
  • Regulatory Landscape: Global data privacy regulations (GDPR, CCPA) and compliance tools.
  • Security: Data encryption, access controls, and penetration testing methodologies.
Qualifications:
  • Education: Bachelor's/Master's in Computer Science, Engineering, or related field.
  • Certifications: AWS/Azure Solutions Architect, Certified Data Engineer, or similar.
  • Experience: 5+ years in solution architecture or technical implementation, with 2+ years in data engineering or enterprise data platforms.
  • Proficient in system design, integration, and implementation across multiple technology domains.
  • Proven track record in deploying scalable financial systems (e.g., payment gateways, digital wallets, stablecoin or cryptocurrency systems preferred).
  • Hands-on experience with cloud platforms (Azure/AWS/GCP), containerization (Kubernetes), and DevOps practices.
  • Excellent communication, collaboration, and critical thinking skills.
  • Understanding of financial regulations, compliance, and security standards.
Expected Deliverables:
  • End-to-end solution architectures for data platforms, including detailed diagrams, technology stack specifications, and integration patterns.
  • ETL/ELT pipeline designs and implementation plans for onboarding new data sources and modernizing legacy systems.
  • Data governance frameworks, including policies for data quality, lineage, and access control, aligned with Enterprise Architecture standards.
  • Technical documentation packages: architecture blueprints, operational runbooks, and security protocols.
  • Prototypes and proof-of-concept implementations demonstrating new data engineering capabilities (e.g., streaming analytics, automated data quality checks).
  • Performance benchmarks and scalability assessments for deployed solutions.
  • Risk mitigation plans, including security audit findings and disaster recovery strategies.