Description
ELT Tech Lead - True Commerce
Department: Delivery
Experience: 8+years
ELT / EDI Lead Engineer (Supply Chain Data Platform – AI-Assisted)
Role Overview
We are 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 will focus on ingesting, normalizing, and modeling EDI-driven transaction data (purchase orders, invoices, shipment notices, acknowledgements) to enable reliable reporting and operational insights.
You will play a critical role in defining how data from multiple trading partners and systems is standardized and interpreted, ensuring consistency in transaction lifecycle tracking, error handling, and KPI reporting.
This is a hands-on leadership role where you will guide data engineers while actively contributing to pipeline development and data modeling.
Key Responsibilities
EDI & Supply Chain Data Ownership
- 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)
ELT Pipeline & Data Modeling
- 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
AI-Assisted Development & Optimization
- 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
Data Quality, Semantics & Governance
- 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
Leadership & Collaboration
- 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
Required Skills & Experience
Core Technical Skills
- 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)
AI-Assisted Engineering (Mandatory)
- Hands-on experience using AI tools such as:
- Cursor (SQL and transformation development)
- GitHub Copilot (code generation and optimization)
- 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
- 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
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