Data Engineer Architect
Full-time
Rooms To Go
We are seeking a Data Architect to provide senior technical leadership in designing and evolving complex, scalable, high-performance data platforms that support advanced analytics, AI/ML, and business intelligence. Leverage deep expertise in Databricks and Azure data ecosystems to define architecture and engineering standards, guide implementation, and ensure solutions are secure, reliable, and built for long-term growth. The Data Architect will shape data strategy, mentor senior engineers, and partner with cross-functional leaders to align technology decisions with business objectives. Responsibilities:
- Lead the architectural design and development of enterprise-grade data platforms using Databricks, Delta Lake, and Azure Data Services.
- Define and enforce technical standards, design principles, and best practices across data engineering to promote consistency, reusability, scalability, and maintainability.
- Architect and optimize modern data warehouse and lakehouse solutions incorporating Snowflake, star schemas, and distributed data systems.
- Guide the integration of real-time and batch data pipelines to support advanced analytics, ML model training, and reporting use cases.
- Design and implement secure, compliant, and high-performance data architectures that support data governance, privacy, and access-control standards.
- Provide technical leadership in implementing infrastructure as code, automated pipeline orchestration, and observability practices.
- Evaluate emerging data technologies, cloud capabilities, and design patterns, recommending adoption where appropriate.
- Mentor senior and mid-level data engineers, promote architectural rigor, and foster a culture of continuous learning and technical excellence.
- Collaborate with data scientists, BI developers, enterprise architects, and business stakeholders to deliver aligned, high-impact solutions.
- Develop and maintain architectural documentation, including design blueprints, system diagrams, and roadmaps.
- Lead proof-of-concept efforts, technical deep dives, and architecture reviews to validate approaches and guide high-risk technical decisions.
- Troubleshoot complex architectural and performance issues within the data ecosystem, ensuring resilience, cost efficiency, and overall system health.
- Promote modern data architecture practices through internal and external forums, technical presentations, and other knowledge-sharing opportunities.
- Perform other duties as required.
- 8-12 years of progressive experience in data engineering, with extensive experience leading the architecture and implementation of large-scale, cloud-native data solutions.
- Expert-level proficiency with Databricks, including Delta Live Tables, Unity Catalog, and Spark performance tuning, as well as Azure Data Services such as Azure Data Factory and Event Hubs.
- Mastery of data modeling, data warehousing, and big data processing, including dimensional modeling, streaming architectures, and data lakehouse patterns.
- Strong understanding of data governance, metadata management, security, and regulatory compliance in cloud environments.
- Familiarity with modern orchestration tools, infrastructure as code-including Terraform and Azure Resource Manager-and monitoring frameworks.
- Deep knowledge of Python, SQL, Spark, and distributed data systems.
- Understanding of how to architect systems that support downstream AI/ML and business intelligence consumption layers.
- Ability to evaluate emerging tools, cloud features, and frameworks and apply them to evolving business needs.
- Proven track record of providing technical leadership on high-impact projects, mentoring senior engineers, and influencing enterprise data strategies.
- Exceptional technical leadership and collaboration skills, with the ability to guide teams and align architecture with business strategy.
- Advanced architectural design skills focused on performance, scalability, resilience, security, and cost optimization.
- Strong analytical and problem-solving capabilities, particularly when addressing complex, cross-platform data challenges.
- Excellent written, verbal, and presentation skills for communicating with technical and non-technical stakeholders.
- Demonstrated ability to influence strategic direction and drive innovation in a fast-paced, evolving technical environment.
- Highly organized, with the ability to manage competing priorities across teams and initiatives.
- Bachelor's degree in computer science, data engineering, information systems, or a related technical field is required; an advanced degree is preferred.
- Industry certifications such as Databricks Certified Data Engineer Professional, Microsoft Fabric Data Engineer Associate, or Azure Solutions Architect Expert are highly desirable.
- 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!
Vacancy posted 7 hours ago
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