Lead Data Architect

Summary The Lead Data Architect will design, build, and operate enterprise data platforms that power GenAI and AI/ML use cases. This highly technical, hands‑on role is responsible for data platform architecture, end‑to‑end data engineering, ML/LLM pipeline design, production model onboarding, and delivery of scalable Databricks‑centric solutions across cloud environments. What You’ll Be Doing Architect and implement enterprise data platforms (batch + streaming) optimized for ML, LLMs, and GenAI workloads. Lead design and hands‑on implementation of Databricks workspaces, Unity Catalog, Delta Lake design patterns, cluster policies, and performance tuning. Build and own end‑to‑end data pipelines (ingest, transform, feature engineering, serving) using PySpark, Databricks Jobs, Spark SQL, Delta Lake, and orchestration tools. Design and operationalize model training, fine‑tuning (LLM), evaluation, deployment, and monitoring pipelines (MLOps/RAG/CAG) integrating Databricks MLflow, CI/CD, and infra‑as‑code. Implement vectorless and vectorization/embedding pipelines, vector store integrations, and retrieval layers for RAG (FAISS, Pinecone, Weaviate, Milvus). Define data schemas, governance, lineage, access controls, and data product APIs; implement Unity Catalog or equivalent for centralized governance. Drive cost/performance optimization for storage, compute (spot/preemptible), and query patterns. Collaborate with engineers, data scientists, product owners, and security to translate business needs into production GenAI solutions. Mentor and lead engineering teams; conduct architecture reviews, code reviews, and run technical deep dives. Implement observability for data and ML pipelines (metrics, logging, data quality tests, alerting). Create reproducible experiment tracking, model registry, and rollout strategies (canary, shadow testing, rollback). Stay current on GenAI/LLM architectures and evaluate/introduce new tooling and frameworks. Required Qualifications BA or BS degree in CS, Computer Engineering, Information Technology or a related field. 8+ years hands‑on experience in data engineering/platform architecture; 3+ years in an architect or lead role. Candidate must hold an active AWS Certified Machine Learning – Specialty certification. Proven, hands‑on Databricks experience (designing workspaces, Delta Lake, performance tuning, productionizing Spark jobs). Deep Spark + PySpark expertise and experience with Databricks Runtime. Strong experience building ML/LLM pipelines and operationalizing models (training, fine‑tuning, serving). Practical experience with vector embeddings, semantic search, and RAG architectures. Solid Python expertise and common ML libraries (PyTorch, TensorFlow, Hugging Face transformers) and MLflow. Cloud platform experience (AWS strongly preferred). Experience with containerization and orchestration while leveraging open source libraries for unstructured and structured data processing, serving/inference. Strong SQL skills; experience with distributed query/warehouse systems and parquet/AVRO/Delta formats. CI/CD and infra‑as‑code experience (Terraform, GitOps, Jenkins/GitHub Actions/GitLab CI). Data governance, security, and IAM experience; experience implementing row/column level access controls and data lineage. Demonstrated ability to design for scalability, reliability, and cost efficiency. Preferred Qualifications Prior experience with Databricks Unity Catalog, Photon, and Databricks SQL. Experience integrating Databricks with vector databases (Pinecone, Neo4j) and retrieval frameworks (LangChain, LlamaIndex). Familiarity with AWS Bedrock or other managed LLM services. Experience with realtime streaming (Kafka, Kinesis) and stream processing on Databricks Structured Streaming. Certifications: Databricks Certified Professional. Experience with data quality and profiling tools (Great Expectations, Soda). Experience with large‑scale ETL frameworks and tools (Airflow, Prefect). Commitment to Non‑Discrimination All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law. Salary Range The proposed salary range for this role is $160,000 to $190,000 USD. This range reflects experience levels and other factors considered by Karsun. Clearance Information This position requires eligibility to obtain a security clearance. The Defense Industrial Security Clearance Office (DISCO) handles and adjudicates the clearance process. More information about Security Clearances can be found on the U.S. Department of State website: Location To be considered for this role, you must reside in one of the following states: CA, CO, DC, FL, GA, IL, MD, NJ, NY, NC, OH, OK, PA, SC, TX, VA, WV. Applicants must be authorized to work in the U.S. We may consider candidates currently in H‑1B status who are eligible for transfer. #J-18808-Ljbffr