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Data Encoder Jobs in Dallas, TX (NOW HIRING)

Wise Skulls

Senior AI/LLM Engineer

Irving, TX · On-site

$100K - $137K/yr

... encoder reranking (BAAI/bge models) FastAPI-based inference services LangChain retriever ... Faithfulness Relevance NDCG MRR Trace-level RAG evaluation (Langfuse) Data Engineering & ETL ...

1 point system

Principal Architect

Irving, TX · On-site

Lead the design, governance, and evolution of reference architectures for web services, APIs, data ... encode enterprise best practices for build, test, security scanning, and release governance.

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Data Encoder information

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$9

$32

$72

How much do data encoder jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for data encoder in Dallas, TX is $32.24, according to ZipRecruiter salary data. Most workers in this role earn between $12.10 and $60.73 per hour, depending on experience, location, and employer.

What is the work of data encoder?

A data encoder is responsible for inputting, updating, and maintaining data in computer systems or databases. They often use software tools like spreadsheets or database management systems and need attention to detail to ensure accuracy and data integrity.

Can I become an encoder with no experience?

Data encoder positions typically do not require prior experience, as training is often provided on the job. Basic skills in typing, attention to detail, and familiarity with data entry tools are helpful for starting in this role.

What is a Data Encoder job?

A Data Encoder is responsible for inputting, updating, and maintaining accurate data in computer systems or databases. They ensure data integrity by verifying and correcting information as needed. The role often involves handling confidential records, organizing files, and generating reports. Strong attention to detail, typing skills, and familiarity with data management software are essential for this position.

What are the key skills and qualifications needed to thrive in the Data Encoder position, and why are they important?

To thrive as a Data Encoder, you need excellent attention to detail, fast and accurate typing skills, and a high school diploma or equivalent as a common minimum qualification. Familiarity with data entry software, spreadsheet applications like Microsoft Excel, and sometimes database management systems is typically required. Strong organization, time management, and the ability to work independently or as part of a team are valuable soft skills in this role. These skills are crucial for ensuring the accuracy, reliability, and efficiency of data processing tasks within various industries.

Is data encoder work hard?

Data encoder jobs typically involve repetitive tasks such as entering and updating information into databases, which can be physically and mentally demanding over long periods. The work requires attention to detail, accuracy, and sometimes working under tight deadlines, but it generally does not involve strenuous physical activity.

What are the typical daily responsibilities of a Data Encoder?

A Data Encoder is primarily responsible for accurately inputting and updating information into digital databases or systems, often working with large volumes of data from paper or electronic sources. Typical daily tasks include reviewing documents for errors, verifying data for completeness and accuracy, and organizing files for easy retrieval. Data Encoders may also collaborate closely with other administrative staff or departments to ensure that records remain up-to-date and accessible. In some organizations, they also assist with basic data analysis or generate routine reports to support business operations.

How much is the salary of a data encoder?

The salary of a data encoder typically ranges from $25,000 to $45,000 per year, depending on experience, location, and the industry. Entry-level positions may start lower, while experienced data encoders with specialized skills can earn higher wages.
What are the most commonly searched types of Data Encoder jobs in Dallas, TX? The most popular types of Data Encoder jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Data Encoder jobs? Cities near Dallas, TX with the most Data Encoder job openings:
Data Encoder jobs near you
Infographic showing various Data Encoder job openings in Dallas, TX as of July 2026, with employment types broken down into 4% Internship, 84% Full Time, 4% Part Time, 4% Contract, and 4% Nights. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $67,054 per year, or $32.2 per hour.
Senior AI/LLM Engineer

Senior AI/LLM Engineer

Wise Skulls

Irving, TX • On-site

$100K - $137K/yr

Contractor

Posted 4 days ago

Job description

Title: Sr AI/LLM Engineer
Location: Irvine, CA (Onsite)
Duration: 6 months (possibility of an extension)
Implementation Partner: Infosys
End Client: To be disclosed
JD:
Overall 8+ years' experience with 5+ years in AI development. PFB the technology skills required. Core Language & Architecture Python 3.11+ Advanced type hints (PEP 484), static typing discipline Async programming (asyncio, async/await, async generators) aiohttp / httpx (async HTTP clients) Pydantic v2 (BaseModel, validation, settings management) Structured logging & tracing patterns Redis (pub/sub, TTL, async clients) REST API design & integration patterns Retry/backoff strategies (Tenacity) Concurrency patterns (parallel tool calls, task orchestration) AI / LLM / Agent Systems LangGraph (state machines, conditional edges, checkpointing) LangChain 0.3.x (LLMChain, StructuredTool, retrievers, prompt templates) ReAct-style agent architectures Tool-based agent design (40+ tool environments) Azure OpenAI / OpenAI APIs (GPT-4o, deployment mgmt, rate limits, token budgeting) Prompt engineering (few-shot, structured output, JSON mode) PydanticOutputParser / structured LLM responses Guardrails / PII redaction patterns Memory abstractions for agents Langfuse (trace instrumentation, evaluation, prompt management) LLM fallback chains & error recovery RAG prompt grounding strategies LLM fine-tuning Neural Network training & tuning Traditional ML models (random forest, k-means clustering, linear regression, etc.) MCP development and consumption Retrieval, Search & RAG Engineering Vector databases (Qdrant and/or Milvus) HNSW indexing parameters Filtering strategies Embedding pipelines (OpenAI ada-002 or equivalent) Batch embedding & re-indexing workflows Hybrid retrieval (BM25 + semantic) Score fusion strategies Cross-encoder reranking (BAAI/bge models) FastAPI-based inference services LangChain retriever abstractions RAG evaluation metrics: Faithfulness Relevance NDCG MRR Trace-level RAG evaluation (Langfuse) Data Engineering & ETL Prefect 2.x / 3.x Flows, tasks, futures Deployments (YAML) Scheduling ETL/ELT design Schema evolution Query optimization OAuth authentication Warehouse/schema management PostgreSQL 16/17 psycopg 3.x Connection pooling SQLAlchemy 2.x (ORM + asyncio) Alembic migrations Advanced SQL Multi-table JOINs CTEs Window functions Timezone conversion Pandas 2.x (complex multi-stage transformations) PyArrow / columnar formats Azure Blob Storage (azure-storage-blob) Document ingestion/parsing: Docling Unstructured python-docx python-pptx DevOps & Platform Docker Linux fundamentals Nice-to-Haves Ray (distributed execution) Columnar performance tuning Network operations domain knowledge NOC / alarm correlation familiarity API & Enterprise Integrations OAuth 2.0 (client credentials flow, token lifecycle) MSAL (browser + service principal flows) Microsoft Graph API SharePoint Outlook Planner OneDrive Pagination App permissions ServiceNow REST API Table API Incident/change mgmt Bulk operations Splunk SDK Saved searches Async queries Log analysis Azure AD app registrations IPAM / OTNA integrations (nice-to-have domain exposure)

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