Sr. AI Data Engineer

HYBRID - Charlotte NC

Have you got what it takes to succeed The following information should be read carefully by all candidates.

Only W2 - No Corp to Corp

OPEN TO SPONSOSRSHIP

PLEASE NO -OPT'S OR EAD'S

MUST HAVE

• Programming: Strong Python and SQL skills.
• Data Engineering: ETL/ELT, data modeling, data integration, batch processing, and streaming pipelines.
• Big Data Technologies: Apache Spark, PySpark, Kafka, or similar technologies.
• Cloud Platforms: AWS, Azure, or GCP.
• Data Platforms: Snowflake, Databricks, BigQuery, Redshift, or Azure Data Lake.
• AI/ML Data Engineering: Experience preparing datasets for machine learning and AI applications.
• Generative AI: Understanding of LLMs, RAG architecture, embeddings, document processing, and vector search.
• Vector Databases: Experience with Pinecone, Weaviate, Chroma, FAISS, or Azure AI Search is desirable.
• Data Formats: JSON, Parquet, Avro, CSV, XML, and other structured or semi-structured formats.
• DevOps: Git, CI/CD pipelines, Docker, orchestration, and automated testing.
• Workflow Orchestration: Airflow, Azure Data Factory, AWS Glue, or similar tools.

Preferred Qualifications

• Experience building data pipelines for Generative AI and enterprise AI solutions.
• Familiarity with frameworks such as LangChain or LlamaIndex.
• Experience with feature engineering, feature stores, and ML data preparation.
• Knowledge of model serving, MLOps, and data observability.
• Experience processing unstructured data, including documents, images, and text.
• Understanding of data governance, PII handling, encryption, and enterprise security. xhyhwjd
• Relevant bachelor's or master's degree in Computer Science, Data Engineering, or a related field.