Cloud Data Engineer, Business Intelligence

Summary

As a Cloud Data Engineer, you will be a key architect of our data ecosystem. You'll own the full software development lifecycle-from initial design and coding to integration testing and deployment. In this role, you aren't just maintaining systems; you are building innovative data applications that empower our organization. We value autonomy and judgment, looking for a professional with 5+ years of experience who is ready to turn complex data challenges into high-performance production solutions. This position will report to the Vice President of Enterprise Data Engineering.

Roles & Responsibilities

• Architect Impact: Design and develop custom data warehouse solutions that serve as the backbone for executive leadership and data science teams, enabling high-stakes, data-driven decision-making.
• Collaborate Across Domains: Partner closely with business analysts, developers, and data scientists to build seamless, user-centric data solutions.
• Cloud-Scale ML and AI Delivery: Transform data science prototypes into scalable, reliable production ML and AI solutions.
• Optimize Performance: Fine-tune and productionize data integration pipelines to ensure maximum efficiency and reliability.
• Build Resilient Systems: Develop proactive "smoke detector" monitoring tools to track and maintain the health of our data ecosystem.
• Lead Project Strategy: Take ownership of work estimates, technical roadmaps, and implementation plans.
• Stay Ahead of the Curve: Research and integrate emerging technologies, products, and development processes to keep our stack competitive.
• Agile Teamwork: Thrive in an agile environment, following best practices and clean coding standards.
• Invest in Growth: Actively grow your personal technical skillset while mentoring others to elevate the entire team.

Skills & Qualifications

• Experience: 5+ years of hands-on experience in data engineering.
• SQL Mastery: Strong experience designing data warehouse solutions with expert-level SQL knowledge.
• Data Architecture: Deep understanding of databases, data structures, and complex data manipulation.
• Pipeline Engineering: Proven ability to create sophisticated data models and end-to-end pipelines for data acquisition, cleansing, and integration.
• The Tech Stack: Deep experience with Microsoft SQL Server and proficiency with Databricks.
• Coding: Proficiency in C# and/or Python.
• Modern Infrastructure: Familiarity with distributed architecture is a significant plus.
• Collaborative Mindset: A track record of success in team-oriented, collaborative environments.
• Communication: Strong interpersonal skills with a focus on delivering excellent support to internal customers.
• Problem Solver: Exceptional analytical skills and a passion for tackling complex technical puzzles.
• Full Lifecycle Knowledge: Comprehensive understanding of the SDLC, including source control and lifecycle management tools.

Additional Preferred Skills

• Azure Ecosystem: Experience with Azure Analytics, Databases, Storage, and AI/Machine Learning services.
• ETL Tools: Experience with SSIS or equivalent enterprise ETL tools.
• Statistical Languages: Familiarity with R.

Educational Requirements

• 4-year degree required