SummaryAs 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 
