ELT / EDI Lead Engineer (Supply Chain Data Platform – AI-Assisted)

Connect Tech+Talent is seeking an experienced ELT / EDI Lead Engineer to lead the design and implementation of data pipelines for a supply chain transaction analytics platform. This role focuses on ingesting, normalizing, and modeling EDI-driven transaction data to enable reliable reporting and operational insights while guiding data engineers in pipeline development and data modeling.

Responsibilities:

• Lead ingestion and normalization of EDI/X12 transaction data (850, 855, 856, 810, 997) across multiple source systems
• Define consistent interpretation of transaction lifecycle states (received, processed, failed, delayed, acknowledged, etc.)
• Standardize data across different trading partners with varying schemas and formats
• Work closely with business stakeholders to define supply chain KPIs (transaction success rates, processing delays, error patterns)
• Design and implement ELT pipelines using Snowflake, Azure data services, or similar platforms
• Define and enforce Bronze (raw), Silver (cleaned), and Gold (analytics-ready) data layers
• Develop transformation logic for structured and semi-structured data (XML, JSON, EDI payloads)
• Ensure pipelines are scalable, reliable, and optimized for performance
• Guide data engineers on best practices for pipeline development and data modeling
• Use AI tools such as Cursor and GitHub Copilot to accelerate SQL development, transformation logic, and pipeline design
• Leverage LLM-based tools to analyze EDI schemas, summarize structure differences, and assist in normalization design
• Use Snowflake Cortex (where applicable) for query optimization, classification (e.g., error grouping), and performance improvements
• Apply AI tools to rapidly prototype transformation logic and refine through manual validation
• Ensure all AI-generated outputs are thoroughly reviewed for correctness, especially in business-critical transaction logic
• Define data validation rules for transaction completeness, accuracy, and consistency
• Ensure alignment between source data and reporting outputs through reconciliation logic
• Establish semantic consistency across KPIs and reporting layers
• Identify and resolve issues related to schema inconsistencies, missing data, and transformation errors
• Provide hands-on technical leadership to a team of data engineers
• Review code, transformation logic, and pipeline implementations
• Collaborate with QA, BI, and DevOps teams to ensure end-to-end data quality and delivery
• Act as a key technical point of contact for stakeholders and delivery leadership

Requirements:

• 8+ years of experience in data engineering, with strong focus on ELT/ETL pipelines
• Deep expertise in EDI/X12 transactions (850, 855, 856, 810, 997) and transaction lifecycles
• Strong hands-on experience with Snowflake, Azure SQL, or similar data warehouse platforms
• Advanced SQL skills for complex transformations and performance optimization
• Experience working with semi-structured data (XML, JSON, EDI formats)
• Strong understanding of data modeling and medallion architecture (Bronze/Silver/Gold)
• Hands-on experience using AI tools such as Cursor (SQL and transformation development), GitHub Copilot (code generation and optimization), and LLM-based tools (schema analysis, documentation, and design support)
• Ability to use AI tools for accelerating SQL development and transformation logic, analyzing complex EDI schemas and identifying patterns, and generating and refining pipeline logic
• Strong ability to validate and refine AI-generated outputs, especially for business-critical transaction data
• Experience working in environments where AI is used to improve productivity while maintaining strict quality standards