Data Engineer Architect

Our Company•Atlanta, GA

About The Position

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.

Requirements

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.

Nice To Haves

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.

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.