Why this role stands out
This hybrid Data Engineer role offers an exciting opportunity to build and maintain the data infrastructure for cutting-edge AI/ML initiatives, allowing you to grow your skills at the intersection of data engineering and applied AI. You will thrive here if you are a mid-senior level professional with strong SQL and Python/Scala skills, eager to contribute to a premier Infrastructure Services client and ensure high-quality data for advanced analytics and AI consumption. Apply now to shape the future of data-driven innovation and gain valuable experience in a dynamic, remote-friendly environment.
Quick overview
Job description
Looking for a Data Engineer to build and maintain the data infrastructure powering our AI/ML initiatives - including data pipelines for model training, retrieval-augmented generation (RAG), and production ML systems. This role sits at the intersection of data engineering and applied AI, ensuring high-quality, well-governed data is available for both traditional analytics and AI consumption.
Responsibilities :
- Design and build pipelines to ingest, clean, and transform structured and unstructured data (documents, PDFs, transcripts, logs) for AI/ML use cases
- Build and maintain vector embedding pipelines and support vector database integration
- Develop feature stores/pipelines for ML model training and inference
- Implement data pipelines supporting RAG architectures - chunking strategies, embedding refresh cycles, metadata tagging
- Partner with ML engineers/data scientists to understand data requirements for model training and evaluation
- Ensure data lineage, quality, and governance across pipelines feeding AI systems
- Optimize pipelines for cost and performance (e.g., Dynamic Tables, streaming ingestion)
- Support MLOps/LLMOps workflows - versioning datasets, tracking data used in model training for reproducibility and compliance
- Implement entitlement/access control logic so AI systems only access data they're authorized to use
- Strong SQL + one of Python/Scala for pipeline development
- Experience with a cloud data platform
- Experience with orchestration tools (Airflow, dbt)
- Understanding of embedding models, vector search, and RAG patterns
- Experience with unstructured data processing
- Familiarity with ML lifecycle concepts
- Experience with Snowflake Cortex, Cortex Search, or similar in-warehouse AI tooling
- Experience in a regulated industry (financial services) with data entitlement/compliance requirements
- Exposure to LLM application frameworks (LangChain, LlamaIndex)
SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work. Please find us at .
SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company to request an accommodation or assistance regarding our policy.
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