IT-Analytics Engineer

Overview

Position Summary

Analytics Engineer is responsible for designing, building, and optimizing a modern manufacturing data platform that transforms complex operational data into trusted, analytics-ready solutions. The position combines hands-on data engineering with technical leadership, leveraging Snowflake, DBT, Matillion, and CI/CD best practices to develop scalable, high-performing data pipelines and models. Working closely with business stakeholders and product owners, the individual will ensure data quality, governance, and observability while building semantic data layers that support reporting, self-service analytics, and future AI-driven capabilities.

The ideal candidate brings deep expertise in modern data architecture, strong communication skills, and experience delivering scalable data products that enable business insights and operational excellence.

Snowflake, Snowflake AI/Cortex, DBT, Matillion, Dimensional Modeling, Data Vault 2.0, Git Hub/CI-CD, Power BI

• Design, develop, and maintain scalable data ingestion and orchestration processes using Matillion or similar enterprise ETL/ELT tools to integrate data from complex manufacturing systems into Snowflake.
• Build, deploy, and support end-to-end data transformation pipelines using DBT and Snowflake, moving data through Bronze (raw), Silver (integrated), and Gold (analytics-ready) layers.
• Develop and maintain Data Vault 2.0 models and related data architecture standards to ensure data is auditable, scalable, and adaptable to evolving business systems and ERP environments.
• Create and optimize dimensional models, star schemas, and semantic data layers that support self-service analytics and high-performance reporting in Power BI and other analytical tools.
• Design, implement, and manage CI/CD processes, source control standards, and automated deployment pipelines using Git Hub Actions, Azure Dev Ops, or similar technologies to ensure reliable and repeatable releases.
• Establish and maintain monitoring, logging, alerting, and observability capabilities to proactively identify, troubleshoot, and resolve data pipeline and platform issues.
• Implement and maintain automated data quality controls, validation testing, and observability frameworks to ensure the accuracy, completeness, and reliability of enterprise data assets.
• Partner with Data Product Owners, business stakeholders, and cross-functional teams to evaluate technical requirements, assess solution feasibility, and translate business needs into actionable technical deliverables.
• Provide technical leadership and guidance on data platform architecture, development standards, best practices, and documentation to ensure scalable and maintainable solutions.
• Define and promote architectural patterns that support future AI, machine learning, and advanced analytics capabilities within the Snowflake ecosystem, including semantic layers, secure data access, search, and agent-based workflows.
• Analyze and optimize Snowflake compute utilization, data processing performance, and SQL query execution to improve platform efficiency, scalability, and end-user experience.
• Collaborate effectively across technical and business teams, communicating complex concepts clearly and contributing to the successful delivery of enterprise data and analytics initiatives.

• Bachelor’s degree in Computer Science, Engineering, or a related field
• 6 years of data engineering and/or analytics engineering experience with demonstrated expertise in Snowflake and DBT.
• Experience querying and consuming data from Microsoft SQL Server (MSSQL) and REST APIs.
• Understanding of data connectivity methods, including ODBC, ADO, and JDBC. Experience with PostgreSQL, MySQL, or MariaDB is a plus.
• Expert experience using Git-based source control workflows and building automated CI/CD deployment pipelines for data platforms.
• Proven experience designing and implementing Medallion/Lakehouse data architectures and dimensional data models.
• Working knowledge and experience with Data Vault 2.0 architecture is preferred.
• Demon…