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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in enterprise data architecture, data modeling, and data governance, with a strong focus on designing scalable data platforms and ensuring compliance with regulatory requirements. Proven ability to lead data integration initiatives and collaborate with stakeholders to define long-term data strategies.
Highest-signal resume keywords
Enterprise Data ArchitectureData ModelingData GovernanceCloud Platforms (Microsoft Azure, AWS, GCP)Data Integration Architecture
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Vault 2.0Conceptual Data ModelingLogical Data ModelingPhysical Data ModelingDimensional Data ModelingDatabase DesignQuery OptimizationPerformance TuningETL/ELT ArchitectureData Processing Architectures
Soft Skills
LeadershipStrategic ThinkingStakeholder ManagementCommunicationProblem-Solving
Tools & Technologies
ErwinER/StudioPowerDesignerVisioHadoopSpark/PySparkHiveKafkaDelta LakeSQL Server
Certifications & Qualifications
TOGAFAzure Solutions Architect ExpertAzure Data Engineer AssociateDatabricks Certified Data Engineer ProfessionalAWS Certified Solutions Architect ProfessionalGoogle Professional Data EngineerSnowflake SnowPro
Industry Keywords
Data Architecture StrategyData Quality ManagementMaster Data ManagementData Compliance FrameworksAPI-Based Data IntegrationEvent-Driven ArchitectureMicroservices ArchitectureData Mesh ConceptsData Fabric ArchitectureData Transformation Initiatives
Tech Stack
Tools & technologiesAWSAzureCloudETLGoogle Cloud PlatformHadoopKafkaMicroservicesMySQLOraclePostgresPySparkSparkSQLVault
About the role
Key responsibilities & impact- Define and implement enterprise data architecture strategy aligned with business objectives
- Design scalable, secure, and high-performing data platforms for analytics, reporting, AI/ML, and operational workloads
- Develop conceptual, logical, and physical data models for enterprise applications
- Architect enterprise data warehouses, data lakes, lakehouses, and modern data platforms
- Establish data governance, metadata management, data quality, and master data management frameworks
- Lead data integration and ETL/ELT architecture across multiple systems
- Define data management standards, best practices, and architectural guidelines
- Collaborate with business leaders, enterprise architects, and technology teams on data transformation initiatives
- Evaluate emerging technologies and recommend data solutions
- Provide technical leadership and mentorship to data engineering and analytics teams
- Ensure compliance with security, privacy, and regulatory requirements
- Lead enterprise data architecture discussions and governance forums
- Drive architecture reviews and design approvals
- Support pre-sales activities, solution proposals, and technical estimations
- Engage executive stakeholders to define long-term data strategies
- Establish reusable architecture standards and frameworks across projects
Requirements
What you’ll need- 12-15 years of experience in designing and implementing enterprise-scale data platforms, data architectures, and data management solutions
- Strong expertise in enterprise data architecture, data strategy and roadmaps, data integration architecture, information architecture, reference architecture development, and data modernization programs
- Extensive experience with conceptual, logical, physical, and dimensional data modeling; Data Vault 2.0; star and snowflake schemas
- Proficiency with data modeling tools such as Erwin, ER/Studio, PowerDesigner, and Visio
- Strong experience designing enterprise data warehouses, data lakes, lakehouse architectures, operational data stores, and data marts
- Strong experience with one or more cloud platforms: Microsoft Azure, AWS, or GCP
- Strong understanding of Hadoop, Spark/PySpark, Hive, Kafka, and Delta Lake
- Experience designing large-scale batch and real-time data processing architectures
- Experience with SQL Server, Oracle, PostgreSQL, Snowflake, Teradata, or MySQL
- Strong expertise in database design, query optimization, data partitioning, and performance tuning
- Strong knowledge of data governance, metadata management, data cataloging, data quality management, MDM, and data privacy regulations
- Experience implementing RBAC, data security policies, and data compliance frameworks
- Experience with enterprise integration patterns, API-based data integration, event-driven architecture, microservices architecture, data mesh concepts, and data fabric architecture
- Ability to create architecture artifacts, solution blueprints, and data flow diagrams
- Strong leadership, strategic thinking, stakeholder management, communication, analytical, and problem-solving abilities
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, Engineering, or a related discipline
- Preferred certifications include TOGAF, Azure Solutions Architect Expert, Azure Data Engineer Associate, Databricks Certified Data Engineer Professional, AWS Certified Solutions Architect Professional, Google Professional Data Engineer, or Snowflake SnowPro
- External qualifications also state Bachelor's or Master's degree in Computer Science, Engineering, Product Design, or a related field and 8-12 years of experience in product development or engineering