Senior Data Engineer
Indexed description
Responsibilities
- Architect and implement complex, scalable data pipelines on Databricks using tools such as Delta Live Tables, Structured Streaming, and Apache Spark
- Lead the design and optimization of modern Data Warehouse Architectures using Snowflake, star schema modeling, and cloud-native best practices
- Collaborate with AI/ML teams to integrate data pipelines for real-time and batch model training, scoring, and monitoring workflows
- Serve as a technical lead on cross-functional projects that incorporate predictive analytics, machine learning, and advanced data transformation
- Develop and implement data governance frameworks, security standards, and compliance controls across data platforms
- Optimize cluster and workflow performance in Databricks to ensure cost-effective and reliable data processing
- Mentor and guide mid-level and junior engineers, supporting their development through code reviews, architectural guidance, and knowledge sharing
- Stay current with industry trends in data engineering, cloud infrastructure, and AI integrations, and identify opportunities for innovation
- Document technical designs, processes, and architectural decisions to promote knowledge reuse and support maintainability
- Performs other duties as required
- 5-7 years of progressive experience in data engineering, with a proven track record of delivering production-grade, cloud-based data solutions
- Proficiency in Python, SQL, Apache Spark, and large-scale data processing frameworks
- Deep hands-on experience with Databricks, Delta Live Tables, and real-time streaming architectures
- Strong understanding of data modeling techniques, including dimensional modeling and star schema design, including implementation patterns for slowly changing dimensions
- Proven experience building and managing cloud-based data environments (Azure preferred; AWS/GCP also valuable)
- Working knowledge of AI/ML lifecycles to design, build and optimize data pipelines that effectively support model training, feature engineering, data versioning, and low-latency inference needs
- Strong grasp of data governance, metadata management, and cloud security best practices
- Experience leading the design and execution of enterprise data transformation initiatives and mentoring technical peers
- Strong analytical and problem-solving skills with the ability to address complex technical challenges independently
- Ability to work effectively in a collaborative team environment and lead technical discussions
- Excellent organizational skills with the ability to manage multiple priorities and meet deadlines
- Proactive mindset and commitment to continuous learning and technical excellence
- Clear and effective written and verbal communication skills
- Bachelor's degree in computer science, data engineering, information systems, or a related field is preferred
- Databricks Certified Data Engineer Professional or Microsoft Fabric Data Engineer Associate certification is required (or must be obtained within 6 months)
- Advanced Databricks certifications (e.g., Machine Learning Professional) are highly desirable
Rooms To Go Benefits
- Medical, dental, and vision insurance
- 401(k) with company match
- Associate discounts including furniture
- Company paid life and disability insurance
- Paid time off
- Employee Assistance Program
- Wellness Programs
- And more!
Applicants must be authorized to work in the U.S.
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