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Full Stack Data Engineer Jobs in Lafayette, LA (NOW HIRING)

NET Full Stack Developer in in our Houston office. Responsibilities * Responsible for implementing ... Dell Boomi for data and application integration * Appian for BPM applications and Apigee for ...

NET Full Stack Developer in in our Houston office. Responsibilities * Responsible for implementing ... Dell Boomi for data and application integration * Appian for BPM applications and Apigee for ...

Senior API Platform Software Engineer

Lafayette, LA ยท On-site

$116K - $153K/yr

Working knowledge of JavaScript/TypeScript for supporting full stack or platform development needs ... This role offers exposure to modern AWS technologies, complex data challenges, AI-enabled ...

Senior API Platform Software Engineer

Lafayette, LA ยท On-site

$117K - $154K/yr

Working knowledge of JavaScript/TypeScript for supporting full stack or platform development needs ... This role offers exposure to modern AWS technologies, complex data challenges, AI-enabled ...

Senior API Platform Software Engineer

Lafayette, LA ยท On-site

$116K - $153K/yr

Working knowledge of JavaScript/TypeScript for supporting full stack or platform development needs ... This role offers exposure to modern AWS technologies, complex data challenges, AI-enabled ...

Senior API Platform Software Engineer

Lafayette, LA ยท On-site

$116K - $153K/yr

Working knowledge of JavaScript/TypeScript for supporting full stack or platform development needs ... This role offers exposure to modern AWS technologies, complex data challenges, AI-enabled ...

Software Developer

Lafayette, LA ยท On-site

$70 - $100/hr

The SDAI team sits at the intersection of software, data, and AI, and is a key driver in how we ... Full-stack engineering * Cloud Infrastructure * Experience managing multiple concurrent projects ...

The SDAI team sits at the intersection of software, data, and AI, and is a key driver in how we ... as a full-stack developerStrong experience with:Application development (web, API, or backend ...

Senior Software Developer

Lafayette, LA ยท On-site

$52 - $68.75/hr

As a senior full stack developer, you will collaborate with the team in an Agile setting to ... data. . The candidate should have experience in web-application development including HTML, CSS ...

SOLUTIONS ARCHITECT

Lafayette, LA ยท Hybrid

$60.25 - $79.25/hr

Company Description Established in 1987, Global Data Systems, Inc. (GDS) is recognized as a leading ... stacks and ability to provide expert advice on solutions/applications. They should also understand ...

SOLUTIONS ARCHITECT

Lafayette, LA ยท On-site

$60.25 - $79.25/hr

Company Description Established in 1987, Global Data Systems, Inc. (GDS) is recognized as a leading ... stacks and ability to provide expert advice on solutions/applications. They should also understand ...

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Showing results 1-20

Full Stack Data Engineer information

See Lafayette, LA salary details

$42.5K

$128.7K

$181.9K

How much do full stack data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for full stack data engineer in Lafayette, LA is $128,704.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $150,900.00 per year, depending on experience, location, and employer.

What is a full stack data engineer?

A Full Stack Data Engineer is a professional who designs, builds, and maintains the entire data pipeline, from data collection and storage to processing and visualization. They work with both the backend infrastructure (such as databases, data warehouses, and ETL processes) and frontend tools (like dashboards or reporting systems) to ensure data is accessible and usable for analytics. Full Stack Data Engineers possess skills in programming, database management, data modeling, cloud platforms, and often data visualization, allowing them to manage every stage of data flow within an organization.

How does a full stack data engineer typically balance responsibilities between backend data infrastructure and frontend data presentation tasks?

Full Stack Data Engineers are often required to split their time between developing robust backend data pipelines and creating user-facing tools or dashboards that visualize data insights. This dual responsibility means you'll need to prioritize tasks based on project needs, effectively collaborating with data scientists, analysts, and frontend developers. Communication is key, as you'll bridge gaps between technical teams and business stakeholders, ensuring data flows seamlessly from source systems to end users. Over time, many engineers find opportunities to specialize further or move into leadership roles overseeing data architecture and team strategy.

What are the key skills and qualifications needed to thrive as a full stack data engineer, and why are they important?

To thrive as a Full Stack Data Engineer, you need strong expertise in data modeling, ETL processes, and proficiency in both backend (e.g., Python, Java) and frontend (e.g., JavaScript, React) development, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), big data tools (like Spark or Hadoop), and database systems (SQL and NoSQL) is typically required, and certifications in these technologies are advantageous. Excellent problem-solving, communication, and collaboration skills help you bridge gaps between data, development, and business teams. These skills ensure you can design, build, and maintain scalable data solutions that meet organizational needs efficiently.

What is the difference between Full Stack Data Engineer vs Data Scientist?

AspectFull Stack Data EngineerData Scientist
CredentialsBachelor's/Master's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science or related fields
Work EnvironmentBuild data pipelines, manage databases, develop APIsAnalyze data, create models, generate insights
Industry UsageTech, finance, healthcare, where data infrastructure is keyResearch, analytics, product development teams

Full Stack Data Engineers focus on building and maintaining data infrastructure, integrating data from various sources, and ensuring data availability. Data Scientists analyze data, develop models, and generate insights. While both roles require strong technical skills, Full Stack Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What are popular job titles related to Full Stack Data Engineer jobs in Lafayette, LA?

For Full Stack Data Engineer jobs in Lafayette, LA, the most frequently searched job titles are:

What job categories do people searching Full Stack Data Engineer jobs in Lafayette, LA look for?

The top searched job categories for Full Stack Data Engineer jobs in Lafayette, LA are:

What cities near Lafayette, LA are hiring for Full Stack Data Engineer jobs?

Cities near Lafayette, LA with the most Full Stack Data Engineer job openings:

Full Stack Developer - Java, React & AI

Srinav Inc.

Lafayette, LA โ€ข On-site

Other

Posted 4 days ago


Job description

Hi,

Pease find the below requirement and send suitable profiles asap.

Role: Full Stack Developer โ€“ Java, React & AI

Location: Lafayette, LA ( Onsite)

Duration: 2+ Years

Full Stack Developer โ€“ Java, React & AI โ€“ Job Description Summary

  1. Strong hands-on experience in React, Java 17+, Spring Boot, Spring Data JPA, Spring Security, and Microservices architecture.
  2. Design and develop scalable REST APIs, event-driven services, and enterprise-grade full-stack applications.
  3. Experience with LLMs, Generative AI, Agentic AI, Prompt Engineering, and Context Engineering.
  4. Build AI-enabled applications using LangChain, LangGraph, OpenAI/Azure OpenAI, and Model Context Protocol (MCP).
  5. Develop RAG solutions using embeddings, vector search, semantic retrieval, and enterprise knowledge sources.
  6. Hands-on experience with Vector Databases such as Pinecone, pgvector, ChromaDB, FAISS, or Azure AI Search.
  7. Strong experience with Redis caching and relational/NoSQL databases including PostgreSQL, Oracle, and MongoDB.
  8. Develop event-driven integrations using Kafka, APIs, microservices, and enterprise integration patterns.
  9. Deploy and manage applications using AWS, Docker, OpenShift/Kubernetes, CI/CD, Git, Maven/Gradle, Jenkins, or GitHub Actions.
  10. Demonstrate strong problem-solving, debugging, performance optimization, collaboration, and end-to-end application ownership.

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Srini

vasuatsrinavdot.net