Lakehouse Reference Architecture
Designed a production-ready lakehouse reference for an LPG shipping company, supporting analytics at scale and forming the basis for future data products and governed datasets.
Overview
Turning data into dependable systems
I work at the intersection of data engineering, cloud architecture and reliability, helping teams move from legacy estates to modern, observable platforms.
Over the last few years I’ve built and supported data platforms for organisations including Anthony Veder, Capgemini, Accenture and AWS. My work ranges from lakehouse design and cloud migration strategy to hands-on pipeline engineering and incident response.
I enjoy taking complex, messy data environments and shaping them into stable, well-instrumented systems that people trust. That usually means combining Databricks, Azure and AWS services with solid engineering practices: version control, CI/CD, monitoring and thoughtful documentation.
I’m especially interested in roles where I can help design and operate large-scale data platforms while mentoring teams and contributing to a culture of sustainable, healthy engineering.
Years of experience
5+ in Data & Cloud
Focus areas
Data platforms · Lakehouse · SRE
Cloud stack
Azure · AWS · Databricks
Certifications
AWS · Databricks · Scrum & more
Experience
Recent roles & impact
Highlights from my work across Anthony Veder, Capgemini, Accenture and AWS.
Senior Data Consultant · Data & AI
- Led the end-to-end data engineering lifecycle within the Data & Analytics team.
- Designed a lakehouse architecture on Azure & Databricks, improving analytics performance by ~30%.
- Built an in-house ETL/ELT framework with CI/CD and observability, reducing MTTR and strengthening SLAs.
- Introduced an SRS template and intake process that brought new dataset onboarding down to ~2 weeks.
Data Solutions Consultant · Insights & Data
- Engineered scalable data pipelines on Azure Databricks, Spark and Azure Data Factory.
- Supported cloud migrations that reduced infrastructure costs by 30%+ and sped up deployments by ~50%.
- Worked with public and private sector clients on ingestion, governance and analytics enablement.
Data Solutions Consultant · Data & AI
- Built reporting pipelines using SSIS, Azure Data Factory and SQL Server, cutting processing time by ~40%.
- Automated workflows that reduced time-to-insight by ~20% for critical business reporting.
Cloud Systems Engineer · Data Eng & Analytics
- Supported 300+ customers across Redshift, Glue, Athena and OpenSearch workloads.
- Improved performance and reduced downtime by ~20%, achieving 96%+ customer satisfaction.
- Helped customers redesign data flows for large datasets, reducing latency by ~30%.
Projects
Selected work
A few examples of the type of platforms and initiatives I enjoy working on.
Multi-Cloud Ingestion Modernisation
Modernised ingestion pipelines for enterprise clients moving from on-prem to cloud, cutting latency and infrastructure costs while improving reliability and data quality.
Redshift Performance Optimisation
Helped multiple AWS customers reshape Redshift workloads, reducing query runtimes and stabilising critical analytics workloads across time zones.
Databricks
Apache Spark
Azure Data Engineering
AWS Analytics
ETL / ELT
SRE & Observability
Certifications
Credentials & continuous learning
A selection of certifications that back up my experience with data platforms and cloud architecture.
AWS Certified Data Analytics – Specialty
AWS Certified Solutions Architect – Associate
AWS Certified Developer – Associate
Databricks Azure Platform Architect
Snowflake Data Warehousing (Hands-on)
Certified Scrum Master (CSM)
Contact
Let’s talk
Interested in data platform engineering, lakehouse projects or cloud reliability work? I’m open to new roles, collaborations and speaking opportunities.
How to reach me
Email is usually the best starting point, and I’m also active on LinkedIn.
Email: ctnatsai@gmail.com
LinkedIn:
linkedin.com/in/natsai-m-b78675111
What I enjoy working on
· Data platform & lakehouse design
· Cloud-native analytics & ingestion modernisation
· Reliability, observability & incident reduction for data systems