Data Lead- Dallas, TX
At a glance
Senior Data Leadership role at Fa Ertb Saasfaprod1. United States · $46,000–$162,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build ETL/ELT flows for structured and unstructured information so LLMs can use it
- Design RAG systems and tune vector stores for fast, relevant retrieval by agents
- Work with AI engineers on chunk sizes and embeddings to improve retrieval coverage and accuracy
- Create cleanup and metadata workflows that remove PII and toxicity and help agents sort information
- Stream fresh data and maintain benchmark datasets and versioned snapshots for agent evaluation
What you bring
- At least ten years in data engineering, including two or more focused on LLM or AI/ML data
- Strong Python skills for data work and API connections, including Pandas, Pydantic and FastAPI
- Hands-on use of a vector database, plus knowledge of similarity search methods
- Experience with modern data platforms and cloud workloads on AWS, Azure or GCP
Who this fits
This senior data engineering role suits someone who has built data systems for LLMs or AI/ML applications and can work across retrieval, quality and streaming. It is not available to independent contractors.
From the employer
We are seeking a Lead Data Engineer to build and scale the data infrastructure powering our Agentic AI products. You will be responsible for the "Ingestion-to-Insight" pipeline that allows autonomous agents to access, search, and reason over vast amounts of proprietary and public data.
Your role is critical: you will design the RAG (Retrieval-Augmented Generation) architectures and data pipelines that ensure our agents have the right context at the right time to make accurate decisions.
Key Responsibilities
- AI-Ready Data Pipelines: Design and implement scalable ETL/ELT pipelines that process both structured (SQL, logs) and unstructured (PDFs, emails, docs) data specifically for LLM consumption.
- Vector Database Management: Architect and optimize Vector Databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) to ensure high-speed, relevant similarity searches for agentic retrieval.
- Chunking & Embedding Strategies: Collaborate with AI Engineers to optimize data chunking strategies and embedding models to improve the "recall" and "precision" of the agent's knowledge retrieval.
- Data Quality for AI: Develop automated "Data Cleaning" workflows to remove noise, PII (Personally Identifiable Information), and toxicity from training/context datasets.
- Metadata Engineering: Enrich raw data with advanced metadata tagging to help agents filter and prioritize information during multi-step reasoning tasks.
- Real-time Data Streaming: Build low-latency data streams (using Kafka or Flink) to provide agents with "fresh" data, enabling them to act on real-time market or operational changes.
- Evaluation Frameworks: Construct "Gold Datasets" and versioned data snapshots to help the team benchmark agent performance over time.
Required Skills & Qualifications
- Experience: 10+ years in Data Engineering, with at least 2 years focusing on data for LLMs or AI/ML applications.
- Python Mastery: Deep expertise in Python (Pandas, Pydantic, FastAPI) for data manipulation and API integration.
- Data Tooling: Strong experience with modern data stack tools (e.g., dbt, Airflow, Dagster, Snowflake, or Databricks).
- Vector Expertise: Hands-on experience with at least one major Vector Database and knowledge of similarity search algorithms (HNSW, Cosine Similarity).
- Search Knowledge: Familiarity with hybrid search techniques (combining semantic search with traditional keyword search like Elasticsearch/BM25).
- Cloud Infrastructure: Proficiency in managing data workloads on AWS, Azure, or GCP.
Preferred Qualifications
- Experience with LlamaIndex or LangChain for data ingestion.
- Knowledge of Graph Databases (e.g., Neo4j) to help agents understand complex relationships between data points.
- Familiarity with "Data-Centric AI" principles—prioritizing data quality over model size.
Compensation, Benefits and Duration
Minimum Compensation: USD 46,000
Maximum Compensation: USD 162,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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