I turn complex data into dependable systems people can trust.

I build resilient data pipelines and decision-ready analytics that power daily decisions for 100+ stakeholders driving a 40% boost in self-service adoption so teams can move faster with confidence.

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How I work

A practical blend of engineering and analysis.

Two disciplines that work together: move data reliably, then make it accessible and decision-ready.

Data Engineering

Scalable ETL/ELT pipelines, orchestration, warehousing, and infrastructure for moving and transforming data at scale.

Apache AirflowSnowflakedbtPythonAWS/Azure

Data Analysis

Self-serve analytics, dimensional modeling, dashboarding, and translating data into decisions for business teams.

TableauPower BISQLLooker StudioDAX
What I bring

The kind of work that helps teams move faster with more confidence.

I connect technical execution with business clarity, turning complex data needs into dependable systems people can actually use.

Reliable data foundations

Pipelines built for scale, observability, and recovery so the team can trust what arrives in production.

Analytics people actually use

Reporting layers structured around real decisions, clear definitions, and dependable metrics.

Insights that drive action

Analytics that translate into clear, confident decisions for the teams that use them.

A pragmatic operator mindset

I combine systems thinking with business context so the technical solution stays useful beyond launch.

Featured projects

Selected projects that balance rigor with clarity.

A sample of the work where data infrastructure and reporting came together to create measurable impact.

Data Engineering

ELT Pipeline at Scale

A 15-source Airflow ELT pipeline moving 2 TB+/day into analytics.

2 TB+/day99.5% uptime40h → 10h/week
Apache AirflowPythonRedshiftAWS
Data Analysis

Self-Serve Sales & Marketing Dashboard Layer

Built dimensional models powering 50+ concurrent BI users.

50+ users15+ data sources99.5% uptime
RedshiftdbtTableauSQL
Data Engineering

DataOps Framework with Quality Monitoring

Automated testing and monitoring reduced errors by 85%.

85% error reductionAutomated validationCI/CD pipeline
DockerGitPythonMonitoring dashboards
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Let's build something reliable

Ready to turn messy data into momentum?

Whether you need a dependable data pipeline or a reporting layer your team trusts, I'd be glad to help.

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