Data Engineer - Dallas, TX
At a glance
Mid-level Data Engineering role at Fa Ertb Saasfaprod1. United States · $38,000–$133,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build ETL/ELT pipelines that prepare structured and unstructured sources for LLM use
- Set up vector databases and tune them to return relevant matches quickly
- Work with AI engineers to refine chunk sizes and embeddings for stronger retrieval
- Create cleaning steps that remove noise, personal data and toxic material from datasets
- Add searchable metadata and stream fresh data; maintain benchmark datasets and snapshots
What you bring
- At least four years in data engineering, including one year on LLM or AI/ML data
- Strong Python skills, with experience in data handling and API integration
- Hands-on use of a vector database and familiarity with similarity-search methods
- Experience with modern data-stack tools and cloud data workloads
Who this fits
This mid-level role suits a data engineer focused on preparing information for AI retrieval and agent workflows. It is for a full-time employee, not an independent contractor.
From the employer
We are seeking a Data Engineer who 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: 4+ years in Data Engineering, with at least 1 year 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 38,000
Maximum Compensation: USD 133,000
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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