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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading data migration projects, designing data architectures, and implementing analytics solutions that drive business insights. Proficient in managing data quality and coordinating stakeholder engagement throughout the project lifecycle.
Highest-signal resume keywords
Data Migration Project LeadershipData Architecture DesignData Pipeline DevelopmentModern Data Engineering PlatformsData Quality Management
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 MigrationData ModelingAnalytics SolutionsPythonPySparkSQLETL/ELT TechnologiesData Quality ManagementPerformance OptimizationSource-to-Target Mapping
Soft Skills
Stakeholder Relationship ManagementTeam DevelopmentBusiness Validation Coordination
Tools & Technologies
DatabricksMicrosoft FabricDelta LakeAzure Data Lake Storage
Industry Keywords
Data FoundationsData InsightsConsulting EngagementsProject DeliveryData Quality Issues
Tech Stack
Tools & technologiesAzureCloudETLPySparkPythonSQL
About the role
Key responsibilities & impact- Lead data migrations from source assessment and planning through transformation, testing and cutover
- Help clients build reliable data foundations and turn data into insights
- Own project delivery, stakeholder relationships and team development
- Lead data-led engagements within consulting or project environments
- Coordinate business validation and sign-off
- Manage data quality issues and defects
- Design and implement data architectures, data models and analytics solutions, including dashboards and reports
Requirements
What you’ll need- Experience translating business requirements into appropriate data architectures, data models and analytics solutions, including dashboards and reports that support decision-making
- Proven experience leading data migration projects or workstreams, from source discovery and profiling through mapping, cleansing, transformation, trial migrations, testing, reconciliation, cutover and post-migration support
- Experience defining migration testing and reconciliation approaches, managing data quality issues and defects, documenting evidence and acceptance criteria, coordinating business validation/sign-off
- Practical understanding of data migration patterns including full and incremental loads, change data capture, source-to-target mapping, reconciliation, cutover and performance optimisation
- Strong hands-on experience with modern data engineering platforms such as Databricks and/or Microsoft Fabric
- Experience managing consulting engagements or multidisciplinary project teams
- Practical experience developing production-grade data pipelines and transformations using Python, PySpark and SQL
- Experience designing and implementing lakehouse or modern data platform architectures, including technologies such as Delta Lake, Azure Data Lake Storage and equivalent cloud-native services
- Hands-on experience with enterprise ETL/ELT and orchestration technologies