Enterprise Cloud Data Engineer

What you'll do:

• ETL/ELT Development: Design, develop, and maintain robust, scalable data pipelines to support both enterprise analytics and the entire machine learning lifecycle.
• Business Solutions: Collaborate with stakeholders across operations, supply chain, finance, and engineering to translate complex business challenges into actionable data requirements and AI-driven solutions.
• Prepare and transform complex datasets into high-quality, model-ready formats suitable for machine learning and Generative AI applications.
• Take full ownership of the data lifecycle for your projects, ensuring high standards of data quality, governance, and reliability from ingestion to consumption.
• Actively contribute to a dynamic, fast-paced environment by proposing new technologies and methodologies to continuously improve our data infrastructure.
• Data Governance
• Integration of key enterprise apps


• AI/ML-Related Responsibilities
• Prototype and develop innovative solutions using Generative AI and Large Language Models (LLMs) to automate workflows and unlock new insights from unstructured enterprise data (e.g., technical documents, financial reports, operational logs)
• Architect and build the data infrastructure required for advanced AI applications, such as implementing pipelines for Retrieval-Augmented Generation (RAG) and managing vector databases to power intelligent search and summarization tools
• Stay at the forefront of the industry by researching, evaluating, and experimenting with emerging AI technologies and platforms to recommend and implement solutions that provide a competitive advantage

What we’re looking for:

• Bachelor’s degree in Computer Science, Information Technology, or a related technical field
• 2+ years of professional experience in data warehousing, ETL/ELT development, and data modeling
• Expert-level proficiency in SQL, including writing complex queries, stored procedures, and performing query optimization
• Strong experience with a modern data warehouse platform such as [e.g., Snowflake, Amazon Redshift, Google BigQuery]
• Demonstrated expertise in ETL/ELT tools and frameworks, such as [e.g., Apache Airflow, dbt, Informatica, Talend]
• Proficiency in at least one scripting or programming language, such as Python, with an understanding of libraries like Pandas or NumPy for data manipulation
• Project management skills
• Great numerical and analytical skills
• Excellent problem-solving skills
• Have attention to detail and excellent communication skills, both written and verbal
• Have an agile mindset to provide solutions quickly with an incremental value to customers

Bonus points for:

• Experience with cloud-based data services and infrastructure (e.g., AWS, GCP, Azure)
• Experience with big data technologies like Apache Spark or Hadoop
• Some Knowledge of data visualization and business intelligence tools like Tableau, Power BI, or Looker
• Experience in a data-centric role supporting machine learning initiatives, including building data pipelines for model training and serving
• Familiarity with ML platforms or feature stores (e.g., SageMaker, Databricks, Feast)
• Familiarity with GenAI platforms such as AWS Bedrock, Gemini
• Exposure to Lowcode platforms such as Mendix, Appsheet

Must-have requirements:

• Ability to occasionally lift up to 50 lbs
• Perform activities such as typing, standing, or sitting for extended periods of time
• Willingness to occasionally travel or work required nights/weekends/on-call
• Work in a facility that contains industrial hazards including heat, cold, noise, fumes, strong magnets, lead (Pb), high voltage, high current, pressure systems, and cryogenics