Data Architect (Databricks)

Data Architect (Databricks) at eNGINE Data Architect (Databricks) at eNGINE in Pittsburgh, Pennsylvania Posted in 1 day ago.

Type:

full-time

Job Description:

eNGINE builds Technical Teams. We are a Solutions and Placement firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build. Our Consulting Workforce is encouraged to enjoy career fulfillment in the form of challenging projects, schedule flexibility, and paid training/certifications. Successful outcomes start and finish with eNGINE . eNGINE has an immediate opening for a Senior Databricks Architect . The primary focus of this role is identifying a senior-level architect with deep, hands-on experience delivering Databricks implementations. This individual will be highly technical, comfortable operating at a detailed execution level, and capable of designing and building robust data platforms in complex environments. Experience working within regulated or compliance-driven settings is preferred but not required. The ideal candidate combines strong technical depth with clear communication, decisiveness, and confidence, and frequently comes from an implementation-focused or consulting-style background.

Role Responsibilities Technical and Architecture Responsibilities:

Lead the architecture and hands-on implementation of Databricks-based data platforms Design lakehouse architectures, data models, and ingestion patterns aligned with enterprise-scale requirements Build, configure, and optimize Databricks environments across cloud platforms (AWS, Azure, or GCP) Develop migration strategies from legacy data platforms to Databricks Create production-ready pipelines using Spark, Delta Lake, and related ecosystem tools Establish security, governance, and performance best practices Troubleshoot complex data platform issues and guide resolution efforts

Delivery and Practice Responsibilities:

Define technical scope and delivery approaches for data platform initiatives Build proofs of concept and reference implementations to validate architecture decisions Create reusable frameworks, templates, and accelerators to improve consistency and delivery speed Contribute to internal standards, patterns, and architectural guidance Support project delivery through technical leadership and oversight Guide and mentor engineering teams through complex implementations

Core Technical Skills:

Extensive hands-on experience designing and implementing Databricks solutions Strong knowledge of Spark, Delta Lake, lakehouse architecture, and modern data platforms Experience working in complex, large-scale, or regulated environments Ability to operate across multiple cloud platforms as required

Professional Skills:

Ability to clearly communicate complex technical concepts to varied audiences Strong architectural judgment and decision-making in ambiguous environments Comfort balancing strategic architecture with hands-on delivery Experience leading engineering teams and guiding technical execution

Success Measures:

Successful delivery of scalable, reliable Databricks implementations Adoption of reusable patterns and standards across the organization Improved delivery velocity and technical consistency Knowledge sharing and contribution to internal centers of excellence Technical growth and enablement of engineering team members