Data Engineer (AI & Automation)

ISI Enterprises is seeking a Data Engineer to build and operate the data platform and infrastructure supporting AI-driven automation across its business units. The role develops secure data pipelines and models, administers Snowflake and AWS infrastructure, and prepares trusted data for AI workflows while supporting governance and reliability.

Responsibilities:

• Design, build, and maintain scalable batch and streaming pipelines that ingest data from internal platforms, SaaS tools, cloud environments, and customer systems. Build reliable ETL/ELT processes with automated testing, validation, and monitoring. Model data in Snowflake (raw, curated, and consumption layers) so it is consistent, documented, and reusable across business units
• Administer and optimize the Snowflake platform, including warehouses, roles and role-based access control, masking and data protection policies, network policies, scheduled tasks, and cost monitoring. Design, deploy, and maintain the supporting AWS infrastructure (e.g., S3, Lambda, ECS, IAM, networking, and secrets management) using Terraform as infrastructure as code. Integrate Snowflake and AWS logging with security monitoring tools such as Microsoft Sentinel
• Partner with the AI Solutions Architect and AI Software Engineer to prepare data for LLM and automation use cases, including retrieval pipelines (RAG), embeddings and vector stores, and structured feature sets. Build the integrations that let AI-driven workflows read from and write back to operational systems. Support evaluation and observability of AI workflows through logging and quality metrics
• Embed secure data practices into every pipeline, including encryption in transit and at rest, least-privilege access, secrets management, data classification, and audit logging. Enforce data segregation and handling requirements for sensitive and controlled information (e.g., CUI). Support CMMC, NIST SP 800-171, and related compliance obligations through documented, auditable data flows
• Monitor pipeline health, performance, and cost in production, and remediate failures quickly. Implement data quality checks, lineage, and alerting. Optimize storage and compute for performance and cost efficiency
• Work with business unit stakeholders to understand operational problems and translate them into data requirements. Contribute through pull requests, code reviews, and agile ceremonies. Write clear technical documentation, including data dictionaries and architecture diagrams, and be prepared to defend design choices to the team. Leverage AI tooling to accelerate development and delivery

Requirements:

• Pursuant to applicable regulations, ISI requires that all candidates for this role present proof of U.S. citizenship before hire
• Ability to obtain and maintain a U.S. Secret clearance
• 4+ years of experience designing, building, and operating data pipelines in production
• Strong proficiency in SQL and Python
• Experience with relational databases, specifically PostgreSQL
• Hands-on experience with Snowflake, including data modeling, RBAC, masking policies, and performance and cost optimization
• Experience designing, deploying, and operating AWS infrastructure (e.g., S3, Lambda, ECS, IAM, VPC networking)
• Hands-on experience with Terraform for infrastructure as code
• Experience with workflow orchestration (e.g., Airflow, Dagster, Prefect) and transformation tooling (e.g., dbt)
• Experience building integrations with REST APIs and third-party SaaS platforms
• Experience using AI tooling such as Claude, Codex, or an equivalent service to develop enterprise software
• Familiarity with version control (Git) and CI/CD practices
• Excellent problem-solving and analytical skills with keen attention to detail
• Ability to work independently and collaboratively in a fast-paced Agile environment
• Strong communication and interpersonal skills, with the ability to interact effectively with team members at all levels
• Bachelor's degree in computer science, data engineering, or a related technical field, or equivalent work or military experience
• Experience preparing data for LLM applications, including RAG pipelines, embeddings, and vector databases (e.g., pgvector, OpenSearch, Pinecone)
• Experience with AWS data services such as Glue, Athena, RDS, and Kinesis, and with AWS GovCloud
• Experience with Snowflake features such as Snowpark, Cortex, scheduled tasks, and Snowflake-to-SIEM log integration
• Experience with containerization (Docker, Kubernetes) and CI/CD for infrastructure deployments
• Experience with streaming technologies (e.g., Kafka, Kinesis)
• Familiarity with data governance, lineage, and cataloging practices
• Familiarity with security frameworks and compliance requirements such as CMMC, NIST SP 800-171, DFARS, or FedRAMP
• Experience working with data from security, IT service management, or MSP tooling (e.g., SIEM, ticketing, PSA/RMM platforms)