Own enterprise data architecture across conceptual, logical, and physical models, including data standards, naming conventions, and best practices.
Design reusable architecture patterns (CDC ingestion, SCD handling, lakehouse/warehouse layers, medallion architecture) and architect scalable ETL/ELT + ingestion frameworks for end-to-end integration and transformations.
Build and optimize warehouse/datamart architectures for analytics and reporting with strong focus on performance tuning (partitioning, clustering, indexing, query optimization).
Ensure data governance, quality, lineage, metadata management, and secure access controls (RBAC, encryption, masking).
Drive architecture reviews, technical decisions, and create/maintain documentation (architecture diagrams, data flows, ERDs, integration specs) ensuring alignment with enterprise standards.
Collaborate with business stakeholders, data engineers, cloud, and BI teams to translate requirements into validated solutions.
Client-facing role with end-to-end ownership of data architecture and delivery in a high-stakes, high-impact environment.

Requirements

Bachelor's or Master's degree in Data Science, Computer Science, or related field.
8-12 years of experience in data engineering or related field.

Applicant Tracking System Keywords

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

Hard Skills & Tools

data architectureETLELTperformance tuningdata governancemetadata managementdata lineagedata modelingarchitecture patternsquery optimization

Soft Skills

collaborationcommunicationtechnical decision-makingdocumentationclient-facingstakeholder managementproblem-solvingownershipalignmentleadership