17.05.2026 aktualisiert


100 % verfügbar
Senior Data Engineer | Snowflake · dbt · Airflow · Python | Azure · AWS · Databricks | AI-Augmented
Wellington, Neuseeland
Nur Remote
MCSE: Data Management and Reporting | Microsoft Certified Solution ExpertÜber mich
Senior Data Engineer with 15+ years in banking, finance and online-sales. I architect Snowflake/dbt platforms and champion AI-augmented development using Cursor, GitHub Copilot & MCP. Available for remote contracts globally.
Skills
dbtSql Data WarehouseCloud-EngineeringData ArchitectureData TransformationData Transformation ServicesDaten-VirtualisierungData WarehousingDatenbankentwicklungInfosphere DatastageDataOpsDatenbank-EnginesAWS Data AnalyticsAzure Data AnalyticsDaten-Pipeline
Snowflake & dbt Data Engineering
Expert-level design and delivery of Snowflake data warehouses and dbt transformation models, including staging, intermediate, and mart layers. Proficiency in Jinja templates, dbt macros, metadata-driven pipeline generation, and Data Vault modeling, reducing manual coding by over 60%.
Cloud Data Platform Architecture (AWS & Azure)
End-to-end architecture and delivery of cloud data platforms on AWS and Azure, including medallion architecture (Bronze/Silver/Gold), AWS Lambda, Step Functions, CDK, CloudFormation, Azure Data Factory, and Azure Data Lake Gen 2. Experience migrating on-premises systems to cloud environments.
Apache Airflow & Pipeline Orchestration
Design and optimization of complex data pipeline orchestration using Apache Airflow, Control-M, and AWS Step Functions. Tuning of multi-schedule dependencies covering 90+ tables and 10+ pipelines, with virtual environment provisioning enabling sub-minute setup times.
Python & SQL Development
Advanced Python scripting for data reconciliation, pipeline automation, and ETL processes. Complex SQL development including stored procedures, transformation logic, and data extraction across SQL Server, Oracle, Redshift, and Snowflake.
Power BI & Analytics Reporting
Development of Power BI semantic models, DAX measures, paginated reports, and deployment pipelines with row-level security and governance controls. Experience with SSAS Tabular models, Power Query, and DAX optimization.
AI-Augmented Development & Prompt Engineering
Application of AI-first engineering practices using GitHub Copilot, Cursor, and MCP (Model Context Protocol) to accelerate dbt model delivery, SQL pipeline generation, and Power BI report development. Creation of structured prompt libraries for dbt macros, SQL refactoring, and reconciliation logic.
CI/CD & DevOps
Setup and management of CI/CD release pipelines for data and Power BI deployments using GitHub Actions, Azure DevOps, and AWS CDK/CloudFormation. Automated failure alerting, retry logic, and infrastructure-as-code provisioning.
Data Vault Modeling
Design and implementation of Data Vault raw vault loading pipelines including CDC (Change Data Capture), data lineage, and business vault business rules. Delivery of reconciliation frameworks validating migration outputs against acceptance criteria.
Spark, Kafka & Streaming
Experience with Apache Spark, Spark Streaming, and Kafka for large-scale data processing. Built Azure Data Factory pipelines processing 7 million semi-structured files using Spark Streaming with config-driven scaling.
Oracle & Legacy System Integration
Senior Oracle development and technical business analysis, including reverse-engineering legacy data warehouses, forward-engineering improved data models, and building custom Power BI visuals using TypeScript and D3.js.
Expert-level design and delivery of Snowflake data warehouses and dbt transformation models, including staging, intermediate, and mart layers. Proficiency in Jinja templates, dbt macros, metadata-driven pipeline generation, and Data Vault modeling, reducing manual coding by over 60%.
Cloud Data Platform Architecture (AWS & Azure)
End-to-end architecture and delivery of cloud data platforms on AWS and Azure, including medallion architecture (Bronze/Silver/Gold), AWS Lambda, Step Functions, CDK, CloudFormation, Azure Data Factory, and Azure Data Lake Gen 2. Experience migrating on-premises systems to cloud environments.
Apache Airflow & Pipeline Orchestration
Design and optimization of complex data pipeline orchestration using Apache Airflow, Control-M, and AWS Step Functions. Tuning of multi-schedule dependencies covering 90+ tables and 10+ pipelines, with virtual environment provisioning enabling sub-minute setup times.
Python & SQL Development
Advanced Python scripting for data reconciliation, pipeline automation, and ETL processes. Complex SQL development including stored procedures, transformation logic, and data extraction across SQL Server, Oracle, Redshift, and Snowflake.
Power BI & Analytics Reporting
Development of Power BI semantic models, DAX measures, paginated reports, and deployment pipelines with row-level security and governance controls. Experience with SSAS Tabular models, Power Query, and DAX optimization.
AI-Augmented Development & Prompt Engineering
Application of AI-first engineering practices using GitHub Copilot, Cursor, and MCP (Model Context Protocol) to accelerate dbt model delivery, SQL pipeline generation, and Power BI report development. Creation of structured prompt libraries for dbt macros, SQL refactoring, and reconciliation logic.
CI/CD & DevOps
Setup and management of CI/CD release pipelines for data and Power BI deployments using GitHub Actions, Azure DevOps, and AWS CDK/CloudFormation. Automated failure alerting, retry logic, and infrastructure-as-code provisioning.
Data Vault Modeling
Design and implementation of Data Vault raw vault loading pipelines including CDC (Change Data Capture), data lineage, and business vault business rules. Delivery of reconciliation frameworks validating migration outputs against acceptance criteria.
Spark, Kafka & Streaming
Experience with Apache Spark, Spark Streaming, and Kafka for large-scale data processing. Built Azure Data Factory pipelines processing 7 million semi-structured files using Spark Streaming with config-driven scaling.
Oracle & Legacy System Integration
Senior Oracle development and technical business analysis, including reverse-engineering legacy data warehouses, forward-engineering improved data models, and building custom Power BI visuals using TypeScript and D3.js.
Erfahrung
Berufserfahrungmehr als 10 Jahre
Freelancer seit2019
Sprachen
EnglishMuttersprache
Projekthistorie
Lead analytics engineering across ASBs data platform, owning end-to-end delivery of dbt models, SQL pipelines, and Power BI reporting assets. Applied AI-prompt-first engineering to accelerate development cycles. Designed and built dbt models implementing staging, intermediate, and mart layers. Wrote and maintained complex SQL Server stored procedures. Built automated reconciliation frameworks comparing Snowflake and SQL Server datasets. Created and managed Control-M job schedules for pipeline orchestration. Developed and maintained Power BI semantic models, DAX measures, and paginated reports. Integrated AI tooling (Cursor, GitHub Copilot, MCP) into the team development workflow.
Delivered end-to-end data platforms and analytics solutions for 10+ organizations across NZ banking, government, and financial services. Led technical design, pipeline architecture, and delivery from requirements through to production dashboards. Specialized in cloud migration (on-prem to Snowflake/AWS/Azure), Data Vault modeling, and metadata-driven pipeline generation. Champion of AI-augmented development practices. Clients: ASB, BNZ, Ministry of Education, Heartland Bank, NZ Superfund, Volpara, OpenPoly.
Built and maintained Snowflake data pipelines using dbt and Apache Airflow. Refactored Scala and PySpark codebases to unified Snowpark code within dbt models. Designed metadata-driven pipeline generation using Jinja templates and macros, reducing manual coding by over 60%. Improved critical dataflow performance by tuning complex dependencies across 4 Airflow schedules and 10+ pipelines covering 90+ tables. Created a custom visual lineage tool adopted team-wide. Built virtual Airflow environments enabling sub-minute environment provisioning. Explored and shared AI-augmented development practices across engineering teams.