Senior Data Engineer

Overview

Advanced Drainage Systems is a leading manufacturer of stormwater and onsite septic wastewater solutions, committed to sustainability and innovation. With a vast manufacturing and distribution network, we deliver high-quality products across multiple industries while recycling over half a billion pounds of plastic annually. At ADS, we foster a culture where diverse perspectives drive better ideas, ensuring every employee feels valued, heard, and empowered to make an impact.

Advanced Drainage Systems (ADS) is seeking an Sr. Data Engineer to design, build, and scale modern data pipelines and AI-ready data platforms that drive operational excellence, manufacturing insights, and advanced analytics across the enterprise.

This role will be a key contributor to ADS’s data modernization initiative, enabling the transition to a cloud-based, scalable architecture that supports AI/ML, IoT data integration, and enterprise reporting. The ideal candidate combines strong data engineering fundamentals with experience preparing data for AI use cases such as predictive maintenance, demand forecasting, and process optimization.

• Design and build scalable ELT/ETL pipelines using cloud-native technologies (e.g., Snowflake, Azure, Databricks)
• Develop and maintain bronze/silver/gold data layers (medallion architecture) for analytics and AI consumption
• Integrate data from ERP, manufacturing systems, IoT sensors, and third‑party platforms into a unified data environment
• Ensure high data quality, reliability, and performance across pipelines

• Engineer datasets optimized for machine learning and AI models
• Partner with data scientists and analytics teams to support predictive maintenance, demand forecasting, and anomaly detection use cases
• Implement data pipelines that support real-time or near-real-time analytics where applicable
• Enable feature engineering and model-ready datasets

• Support migration from legacy platforms (e.g., SQL Server/SSAS) to modern cloud data platforms
• Build and maintain integrations using tools such as Informatica, APIs, and streaming frameworks
• Contribute to architecture patterns that enable scalable and reusable data products

• Implement and enforce data governance standards, lineage, and metadata management
• Ensure compliance with data security and privacy policies
• Monitor and improve data quality and pipeline performance metrics

• Partner with business stakeholders (Manufacturing, Supply Chain, Sales) to understand data needs
• Work closely with analytics engineers, BI developers, and SMEs to deliver trusted data assets
• Translate business requirements into scalable data solutions

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
• 3–7+ years of experience in data engineering or data platform development
• Strong proficiency in SQL and Python
• Hands‑on experience with cloud data platforms (Snowflake, Azure, or AWS)
• Experience building ETL/ELT pipelines and data models
• Familiarity with data warehousing concepts and medallion architecture

• Experience supporting AI/ML workflows or data science teams
• Knowledge of manufacturing, supply chain, or IoT data environments
• Experience with Informatica, Databricks, or streaming technologies (Kafka/Event Hub)
• Understanding of data governance frameworks and data quality tools
• Exposure to Power BI or modern BI tools

• Strong problem-solving and analytical thinking
• Ability to balance speed, quality, and scalability in delivery
• Excellent communication skills across technical and business audiences
• Ownership mindset with focus on measurable outcomes and ROI

• Opportunity to help build a modern, AI-enabled data platform from the ground up
• Direct impact on manufacturing optimization, product innovation, and customer insights
• Work with a growing Enterprise Analytics team driving enterprise-wide transformation

• Delivery of production-ready pipelines supporting key…