Senior Data Engineer
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Key skills for this role
About the Role
Cander seeks a Senior Data Engineer to architect and develop core data infrastructure for AI-driven supply chain solutions. The role involves designing defense-grade Data Lakehouse architectures, integrating SAP S/4HANA and Ariba, and building pipelines for generative AI.
Key Skills for This Role
Responsibilities
- Design and deploy defense grade Data Lakehouse architectures as Single Source of Truth for AI driven Supply Chain Intelligence
- Lead technical execution of Workstream 1: Data & Platform Foundations, integrating SAP S/4HANA, Ariba, and unstructured data
- Architect and deploy ingestion pipelines for high volume transactional data from ERP systems
- Build connectors for external market intelligence feeds to enrich procurement data
- Design and implement standardized procurement data model and taxonomy
- Engineer pipelines to ingest and transform unstructured technical data into vector ready formats for RAG applications
- Manage and optimize Vector Databases for high speed retrieval
- Establish data lineage and traceability protocols for Model Based Systems Engineering
- Implement RBAC, audit logging, and data redaction policies for compliance
- Deploy automated data quality frameworks for BOM and cost data
Requirements
- 5+ years of experience in Data Engineering, with at least 2 years focused on building pipelines for Machine Learning or Generative AI applications
- Expert proficiency in Python, SQL, and modern data engineering frameworks including Apache Spark, Kafka, and Airflow
- Strong experience extracting data from complex ERP environments, specifically SAP S/4HANA and SAP Ariba
- Deep understanding of Data Lakehouse architectures (Databricks/Delta Lake), Relational Databases (PostgreSQL), and Vector Databases (Weaviate/Milvus)
- Experience building pipelines for RAG solutions, Conversational AI agents, and classical ML models
- Proficiency with containerization (Docker, Kubernetes) and CI/CD pipelines
- Experience in Supply Chain, Manufacturing, or Defense sectors
Full Job Posting
Job Summary
- We are seeking a Senior Data Engineer to architect and develop the core data infrastructure that will underpin our AI driven transformation.
- You will design and deploy high security Data Lakehouse environments, establishing a single, authoritative source of truth for our AI systems.
- You will lead the technical implementation of 'Workstream 1: Data & Platform Foundations,' a critical initiative for our flagship projects.
Key Responsibilities
- Design and deploy defense grade Data Lakehouse architectures to serve as the Single Source of Truth for AI driven Supply Chain Intelligence.
- Lead the technical execution of Workstream 1: Data & Platform Foundations, mapping rigid enterprise systems (e.g., SAP S/4HANA, Ariba) and collaborating with cross functional teams.
- Architect and deploy ingestion pipelines to extract high volume transactional data from ERP systems like SAP S/4HANA, Ariba, and PLM.
- Build connectors for external market intelligence feeds (e.g., S&P Global, Orbis, EcoVadis) to enrich internal procurement data.
- Design and implement a standardized procurement data model and taxonomy across multiple entities.
- Engineer pipelines to ingest, process, and transform unstructured technical data (PDF tender documents, CAD metadata, historical CONOPS) into vector ready formats for RAG applications.
- Manage and optimize Vector Databases (e.g., Weaviate) to store embeddings of archival proposals and engineering snippets.
- Establish data lineage and traceability protocols to link requirements to physical components, supporting MBSE and Digital Thread implementation.
- Implement Role Based Access Control (RBAC), audit logging, and data redaction policies to ensure compliance with export controls and on premise security requirements.
- Deploy automated data quality frameworks to validate Bill of Materials (BOM) completeness and cost data accuracy before ingestion into AI models.
- Optimize data pipelines for on premise GPU clusters and air gapped environments.
- Operate within a structured Sprint Zero environment to ensure data lineage, security, and governance meet defense grade standards.
Qualifications And Experience
- 5+ years of experience in Data Engineering, with at least 2 years focused on building pipelines for Machine Learning or Generative AI applications in an enterprise setting.
- Expert proficiency in Python, SQL, and modern data engineering frameworks including Apache Spark, Kafka, and Airflow.
- Strong experience extracting data from complex ERP environments, specifically SAP S/4HANA and SAP Ariba, with familiarity in SAP BTP as a plus.
- Deep understanding of Data Lakehouse architectures (Databricks/Delta Lake), Relational Databases (PostgreSQL), and Vector Databases (Weaviate/Milvus).
- Experience building pipelines for RAG solutions, Conversational AI agents, and classical ML models using tools such as dbt, dagster, or prefect.
- Proficiency with containerization (Docker, Kubernetes) and CI/CD pipelines for deploying data workflows in secure environments.
- Experience in Supply Chain, Manufacturing, or Defense sectors, with the ability to understand 'Bill of Materials' (BOM) structures and procurement lifecycles.
- Ability to navigate the governance challenges between agile data work and rigid systems engineering requirements.
- Proven ability to collaborate with Data Scientists and Backend Engineers to define data schemas that support predictive modeling and AI agents.
Technical Skills
- Expert proficiency in Python and SQL for data engineering tasks.
- Strong experience with modern data engineering frameworks, including Apache Spark, Kafka, and Airflow.
- Deep expertise in extracting and processing data from complex ERP environments, specifically SAP S/4HANA and SAP Ariba.
- Comprehensive understanding of Data Lakehouse architectures, such as Databricks and Delta Lake.
- Experience with relational databases, including PostgreSQL, and vector databases like Weaviate and Milvus.
- Proven ability to develop data pipelines for RAG solutions, conversational agents, and classical ML models using tools like dbt, Dagster, or Prefect.
- Proficiency in containerization technologies, including Docker and Kubernetes, and experience implementing CI/CD pipelines.
- Knowledge of defense grade security protocols, including RBAC, audit logging, and data redaction policies.
- Experience building and optimizing pipelines for high performance GPU clusters and air gapped environments.
- Familiarity with automated data quality frameworks to validate critical datasets such as BOM and cost data.
- Ability to design and implement standardized procurement data models and taxonomies.
- Experience engineering pipelines for unstructured data ingestion, including PDF tender documents, CAD metadata, and historical CONOPS.
Project Focus: Supply Chain Intelligence & Platform
- The client is seeking a Senior Data Engineer to design and construct the foundational data infrastructure for an AI driven transformation.
- You will lead the technical execution of 'Workstream 1: Data & Platform Foundations,' a critical component of the organization’s flagship initiatives.
- All work will be conducted within a structured 'Sprint Zero' environment, ensuring rigorous data lineage and security compliance with defense grade standards.
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