jared@platform:~$ whoami
Jared Sloan
Senior Data Platform Engineer
company
CVS Health — remote, New Haven, CT
background
SQL Server DBA (healthcare / HL7 data exchange) → multi-cloud data platform engineering
education
MS, Central Connecticut State University · BS, UMass Lowell

I build reliable, scalable data systems — from SQL Server internals to cross-cloud database evaluation, keyless cloud identity, and applied AI tooling in production pipelines.

// core

Stack

Databases

  • SQL Server (production DBA, HA/DR)
  • Azure SQL / Managed Instance
  • PostgreSQL
  • Google Cloud AlloyDB (evaluation)

Cloud

  • Azure, AWS, GCP
  • OIDC / Workload Identity Federation
  • Cost governance & FinOps
  • Infrastructure as code

Platform & Automation

  • CI/CD (GitHub Actions)
  • ETL / SSRS / SSIS
  • Python, PowerShell
  • SAFe Agile delivery

Applied AI

  • Agentic pipelines in CI
  • Google AI Studio / Gemini API
  • LLM-driven research tooling
  • Cost-bounded automation design
// credentials

Certification path

Held
SAFe Practitioner
Scaled Agile delivery.
Held — Oct 2025
Cisco: Introduction to Cybersecurity & Networking Basics
Foundational security literacy alongside the data-platform core.
In progress
DP-300
Azure Database Administrator Associate — a direct extension of the SQL Server DBA background onto Azure SQL.
Planned next
DP-700
Fabric Data Engineer Associate — Microsoft's current data-engineering credential (replacing the retired DP-203) and the natural complement to DP-300: administering and building the platform.
// evidence

Applied, not just titled

A title says what the role is. This is what the work actually looks like, drawn from real personal infrastructure projects — not hypotheticals.

Multi-cloud OIDC / Workload Identity Federation, hand-built across three providers
Azure, AWS, and GCP, each with least-privilege, purpose-scoped identities per workflow — no long-lived stored credentials in CI, the pattern enterprise platform teams are standardizing on.
Repeatable cross-cloud cost-audit method
A documented, re-runnable process classifying every resource across three clouds as free / billed-negligible / real-cost-risk — FinOps discipline applied to a real multi-cloud footprint.
Agentic AI pipelines running in production CI
Headless LLM automation with explicit cost/quota controls — practical experience with the exact "agentic AI in real workflows" gap most candidates only have surface exposure to.