Architect enterprise-wide data solutions spanning relational, flat file, IoT, and event-based sources
Design and build scalable data pipelines, leveraging modern cloud tools and best practices
Transform raw and OT data—sensor, time-series, and event streams—into reusable data products
Guide secure data movement across highly segmented and sensitive environments
Modernize legacy data patterns, recommending new approaches aligned to modern frameworks
Produce architecture diagrams and artifacts for governance and technical review boards
Collaborate with OT teams, architecture peers, and business data owners to drive adoption
Lead modernization initiatives and influence stakeholders through technical credibility
Research, evaluate, and recommend emerging technologies and best-fit architectural patterns

Requirements

7–9+ years in data architecture or advanced data engineering roles
Strong proficiency in data architecture and data modeling
Expertise in ETL, ELT, and modern data pipeline engineering
Hands-on experience with Databricks and AWS (or similar cloud ecosystem)
Experience working with structured, unstructured, event-driven, and time-series data
Ability to design, interpret, and present architecture diagrams and system blueprints
Strong understanding of data governance, security, and secure data movement practices
Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedata modelingETLELTdata pipeline engineeringDatabricksAWSdata governancedata securityarchitecture diagrams

Soft Skills

collaborationleadershipinfluencetechnical credibility