Build agents

This service introduces Build Agents, a class of autonomous, AI-powered agents purpose-built to generate, validate, execute, and convert data platform code artifacts across the modern data stack. These agents close the loop from design to deployment by translating approved models and mappings into executable code, optimising implementation velocity and quality assurance. Build Agents operate across a variety of data engineering environments (SQL, Python, Spark, DBT, etc.) and target data platforms (e.g. Snowflake, Databricks, BigQuery, Synapse). They: Generate ETL/ELT logic from mappings and model specifications. Perform intelligent code reviews and enforce architectural guardrails. Execute and validate workloads in target platforms. Convert legacy code into modern equivalents (e.g. Informatica to Spark, PL/SQL to dbt, SSIS to Python). Integrate with CI/CD and DevOps pipelines to enable production-grade automation. The solution is designed to run entirely on AWS utilising the following AWS services:

Amazon S3

Amazon Bedrock

Amazon DynamoDB

Amazon OpenSearch Service

Amazon ECR

Amazon ECS / AWS Fargate

Who is it for?

The Build Agents service is aimed at data engineering teams and platform owners responsible for implementing modern data pipelines and workloads under tight timelines and with high code quality requirements. Key user groups include: Data Engineers / Developers: Looking to reduce time spent on boilerplate code and refactoring. Platform Engineering Teams: Wanting scalable, consistent implementation aligned to platform standards. Modernisation Program Teams: Seeking to accelerate delivery across multiple domains or workstreams. Architecture and Quality Assurance Functions: Aiming to enforce reusable patterns, security, and performance standards.

How Does It Work?

Build Agents: Core Capabilities Build Agents consume inputs such as: Source-to-target mappings and logic specifications (from Design Agents). Target platform configurations and development frameworks. Legacy codebases for conversion and reverse engineering. Using a combination of LLMs, static analysis, execution feedback, and agentic orchestration, Build Agents can: Generate code for staging, transformation, and data loading layers (e.g., dbt models, Spark jobs, SQL scripts). Conduct code reviews, checking for performance, logic validity, security vulnerabilities, and best practice alignment. Deploy and test workloads on data platforms, with feedback loops on success/failure. Convert code from legacy systems into modern equivalents, preserving logic and intent. Package and version code for seamless integration into production pipelines.

Value Proposition

Code Generation at Scale – Accelerates delivery with machine-generated code tailored to enterprise platforms. Automated Quality Assurance – Embeds reviews and validations into the build process, improving reliability and compliance. Legacy Code Modernisation – De-risks migration by preserving logic while transforming outdated codebases into modern formats. Execution-Integrated Automation – Executes and validates directly within target platforms, closing the feedback loop. DevOps Alignment – Produces production-ready code with proper structure, documentation, and CICD integration.