Thaneegan
Chandrasekara
THANEEGAN CHANDRASEKARAToronto, Ontario
Technical Platform Manager at Adobe

Enterprise automation.
Governed AI.
Reliable platforms.

I combine hands-on cloud engineering with enterprise platform leadership to make complex systems reliable, secure, and useful.

Explore my experienceDownload resume PDF
Thaneegan Chandrasekara
Engineering mindset.Enterprise perspective.
AUTOMATE. GOVERN. SCALE.Cloud engineering + platform leadership
Skills & technologies
Tools & technologiesCapabilities & practices
Swipe through categories

Cloud & Infrastructure

Tools & technologies

  • GCP
  • AWS
  • Terraform
  • Docker
  • Kubernetes
  • Virtual Machines
  • Linux

Capabilities & practices

  • Infrastructure as Code
  • Environment Provisioning
  • Cost Optimization

DevOps & Delivery

Tools & technologies

  • GitLab CI/CD
  • GitHub Actions
  • Jenkins
  • Ansible
  • Bash
  • Grafana
  • New Relic

Capabilities & practices

  • CI/CD
  • Observability
  • Deployment Automation

AI & Automation

Tools & technologies

  • Claude Code
  • ChatGPT
  • OpenAI Codex
  • Microsoft Copilot

Capabilities & practices

  • Generative AI
  • AI Governance
  • LLM Workflows
  • Prompt & Workflow Design
  • Human-in-the-Loop Review
  • AI Use-Case Evaluation

Data & Analytics

Tools & technologies

  • Python
  • PostgreSQL
  • Power BI

Capabilities & practices

  • Data Pipelines
  • Data Integration
  • KPI Reporting
  • Caching
  • Snapshot Strategies

Software Development

Tools & technologies

  • Java
  • TypeScript
  • JavaScript
  • Next.js
  • FastAPI

Capabilities & practices

  • Full-Stack Development
  • API Integration

Enterprise Platforms

Tools & technologies

  • Adobe Workfront
  • Workfront Fusion
  • Airtable
  • Boomi
  • ServiceNow
  • AEM
  • WorkBoard
  • Adobe Admin Console

Identity & Security

Tools & technologies

  • Okta
  • CyberArk

Capabilities & practices

  • IAM
  • API Governance
  • Access Governance
  • Service Account Management
  • Credential Rotation

IT Service Management

Capabilities & practices

  • Release Management
  • Change Management
  • Incident Management
  • Knowledge Management
  • Risk Management
  • ITIL-aligned practices
01 / CAREER EXPERIENCE

Engineering depth.
Enterprise leadership.

Two sides of my work: building the technical foundations and leading the platforms that depend on them.

Adobe2023 — PRESENT
Technical Platform Manager · Current
Previously Cloud Platform Engineer

Enterprise platforms.
Governance at scale.

Platform ownership · Responsible AI adoption · Release leadership

Challenge
Keep enterprise automation platforms reliable and governed while evolving their capabilities and enabling AI adoption.
My contribution
I own strategy, roadmaps, access and identity governance, operational health, and release delivery across Workfront, Fusion, Airtable, and WorkBoard. I also evaluate AI use cases and product betas for enterprise readiness.
Outcome
Delivered 70+ production releases in FY25 under formal validation and change controls, and built daily reporting pipelines for operational and leadership insights.
Leadership with technical depthGovernance, reliability, AI enablement, and cross-functional delivery
Workfront & FusionIAMAI governancePower BINew Relic
Loblaw2021 — 2023
DevOps Engineer I & II
Cloud infrastructure & delivery automation

Lab in the Sky.
Infrastructure on demand.

Cloud engineering · Infrastructure as Code · CI/CD

Challenge
New lower environments took 4+ days to provision, with application setup and delivery needing greater repeatability.
My contribution
I designed the cloud modernization proof of concept and automated GCP VM environments with GitLab CI/CD and Terraform. I used Ansible, Docker, Java, Bash scripting, and cloud IAM/access controls across provisioning, configuration, and deployments.
Outcome
Reduced provisioning to under one hour. Containerized pharmacy application components and enabled standardized Lab in the Sky environments, supported by monitoring and cost controls.
Provisioning before4+ days
Provisioning after< 1 hour
GCPTerraformAnsibleDockerVMsIAMGitLab CI/CDJavaBash
Full career timelineRoles, dates & earlier experience
NOV 2024 — PRESENTTechnical Platform ManagerAdobeCurrent

I own enterprise strategy, governance, administration, and operational health across Adobe’s automation platforms.

  • Lead AI enablement, platform roadmaps, access and identity governance, release management, analytics, and reliability.
  • Delivered 70+ production releases in FY25 across Workfront Automation, Boomi, and enterprise systems.
  • Built daily Power BI reporting pipelines combining AEM Assets, Workfront, Snowflake, and other enterprise sources.
  • Evaluate internal AI product betas for enterprise use cases, governance, operational impact, and rollout readiness.
Workfront & FusionAirtableWorkBoardPower BI
OCT 2023 — NOV 2024Cloud Platform EngineerAdobe

Established the operational foundations for enterprise automation systems.

  • Led platform administration, access provisioning, scenario reviews, service accounts, and production deployments.
  • Designed release processes, governance controls, and production validation standards.
  • Architected monitoring and reliability frameworks with New Relic, including alerting standards and performance baselines.
  • Developed incident-response procedures and runbooks, and partnered with engineering teams on AI-enabled product betas.
New RelicBoomiObservabilityIncident response
FEB 2022 — SEP 2023DevOps Engineer IILoblaw Companies Limited

Transformed lower-environment delivery from manual setup to automated cloud infrastructure.

  • Reduced new-environment provisioning from 4+ days to under one hour.
  • Automated on-demand GCP environments using GitLab pipelines and Terraform, with Ansible for deployments.
  • Built Grafana/PostgreSQL dashboards and automated cost and utilization reporting.
  • Containerized pharmacy application components including Tomcat services, IBM DB2, IBM MQ, RabbitMQ, and microservices for Lab in the Sky environments.
GCPTerraformAnsibleGrafana
MAY 2021 — FEB 2022DevOps Engineer ILoblaw Companies Limited

Modernized build, deployment, and configuration workflows for pharmacy applications.

  • Automated delivery with Bash, Jenkins, Ansible, and GitLab pipelines.
  • Transitioned from licensed Pivotal Tomcat and AdoptJDK to Apache Tomcat 9 and OpenJDK.
  • Supported Linux environments and designed the on-premise-to-cloud modernization proof of concept later implemented as Lab in the Sky.
LinuxJenkinsGitLabJava
2018 — 2019Earlier engineering experienceLoblaw Companies Limited · Internships

Team Delivery Lead · May–August 2019

Led a four-month transformation of legacy components to microservices, coordinating delivery, risk management, Kanban practices, and team cadence.

IT Analyst · May 2018–April 2019

Led a rollout to 7,000+ retail store workstations, resolved production issues, authored knowledge-base articles, analyzed performance with Dynatrace, and contributed to workstation modernization.

02 / PERSONAL PROJECTS

Curiosity.
Built into a product.

SportsDawgs brings together AI-assisted development, workflow automation, and data analysis in a personal full-stack project.

INDEPENDENT PROJECTSEP 2025 — PRESENT

SportsDawgs.

Fantasy basketball analytics.

Challenge
Bring league, player, and schedule data together so fantasy decisions can reflect a manager’s scoring strategy.
My contribution
I use AI-assisted development to build the product, automate data workflows, and turn Yahoo Fantasy and NBA data into customizable analysis.
Outcome
A full-stack platform with player and team comparisons, matchup analysis, draft tools, scoring models, and repeatable snapshot pipelines.
AI-assisted developmentData analysisAutomation
Explore technical detailsLive link coming soon
SPORTSDAWGS / DATA FLOW

From raw data to fantasy decisions.

Automated refreshes keep the data consistent. Custom scoring turns it into analysis managers can explore.

  1. 01Source dataYahoo Fantasy + NBA data
    • League & roster data
    • Game schedules
    • Player boxscores
  2. 02Ingest & refreshAutomated workflows
    • Schedule ingestion
    • Boxscore synchronization
    • Baseline refreshes
  3. 03Store & preparePostgreSQL + snapshots
    • Nightly snapshots
    • Caching strategy
    • Consistent shared data
  4. 04Score & compareFastAPI + Python
    • Custom player/team scoring
    • Punt & focus preferences
    • Value & impact rankings
  5. 05Explore & decideNext.js + TypeScript
    • Player & team comparisons
    • Weekly matchups
    • Draft & transaction analysis
What shapes the analysis?Refreshed datasets + each manager’s scoring strategy and punt/focus preferences.
Technical detailsData pipelines, scoring & product design
THE SYSTEM

Consistent data, less repeated compute.

Nightly snapshots, schedule ingestion, baseline refreshes, and boxscore synchronization feed a caching strategy that keeps multi-user data consistent.

THE ANALYTICS

Scoring that fits the strategy.

Customizable player and team scoring includes punt/focus logic, impact rankings, and z-score/value-based overall rating modes.

THE EXPERIENCE

Built to explore and compare.

Player, Team, Weekly Matchups, Draft, Transaction Analyzer, and comparison dashboards combine sortable heatmaps, dynamic filters, and quick-compare workflows.

03 / CERTIFICATIONS

Credentials.

GOOGLE CLOUD

Associate Cloud Engineer

GOOGLE CLOUD

GCP Digital Cloud Engineer

ADOBE

Workfront Developer

04 / SKILLSETS

The skills behind
the work.

01

Cloud & infrastructure

Capabilities & practicesCloud environments, infrastructure automation, access controls, and observability.

Tools & technologies

  • GCP
  • AWS
  • Terraform
  • Virtual Machines
  • Docker
  • Kubernetes
  • Ansible
  • New Relic
  • Grafana
02

Engineering & data

Capabilities & practicesDelivery pipelines, full-stack applications, data analysis, and operational automation.

Tools & technologies

  • GitLab CI/CD
  • GitHub Actions
  • Jenkins
  • Java
  • Bash
  • Python
  • TypeScript
  • Next.js
  • FastAPI
  • PostgreSQL
  • Power BI
03

AI & platform leadership

Capabilities & practicesAI-assisted workflows, use-case evaluation, human review, governance, and release management.

Tools & technologies

  • Claude Code
  • ChatGPT
  • OpenAI Codex
  • Microsoft Copilot
  • Adobe Workfront
  • Workfront Fusion
  • Airtable
  • Boomi
  • WorkBoard
05 / A LITTLE ABOUT ME

An engineer’s curiosity.
A builder’s mindset.

I enjoy turning complex systems and repetitive work into something people can use with confidence. That connects my cloud engineering background, my platform leadership at Adobe, and the products I build independently.

SportsDawgs brings that same curiosity to fantasy basketball: combining AI-assisted development, automation, and data to explore better decisions.

06 / EDUCATIONBachelor of EngineeringHonours SoftwareMcMaster University · Hamilton, Ontario
07 / GET IN TOUCH

Let’s build
what’s next.

For conversations about AI, automation, platform leadership, or engineering.

Say helloLinkedIn

Based in Toronto, Ontario, Canada