Aakash Patel

Data Engineer

Canada0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building automated data pipelines.
Proficient in AI solutions for real-world problems.
Strong background in data engineering and architecture.

Stackforce AI infers this person is a Data Engineer specializing in SaaS and Fintech solutions with a focus on automation and AI.

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Skills

Core Skills

Data Engineering

Other Skills

Python (Programming Language)Azure AI FoundryWeb ScrapingDocumentation AutomationData ArchitectsAzure Data FactoryETL ToolsAzure Synapse AnalyticsData ArchitectureLangChainAzure DatabricksCopilot Agent BuilderData InfrastructureMicrosoft CopilotMicrosoft Azure

About

Data Engineer by craft. AI builder by obsession. Automation addict by choice. My brain refuses to accept friction as normal. If something is slow, I want to speed it up. If it's manual, I want to automate it. If it's messy, I want to make it elegant and repeatable. I build things that make work lighter — data pipelines, agentic AI solutions, LLM-powered workflows, and automation tools that quietly save hours every day. At Avenue Living, I built an agentic AI system that autonomously scrapes the web, finds company data, and pushes it into HubSpot — no human in the loop. I also integrated Claude LLM via Azure AI Foundry to auto-generate documentation on every code release. This is the kind of work I love: real AI, solving real problems, at scale. Outside work, I build things for myself too. I created an automated LinkedIn content system — it searches the web for trending tech topics, generates hooks and posts using Claude, refines them further with OpenAI, and auto-publishes to LinkedIn via API. No manual work, start to finish. That's just how my brain works — if I can automate it, I will. Master's in Big Data Analytics. Builder of automated systems. Lifelong student of "there must be a better way." Open to conversations about data, AI, or automation — reach out: aakash98.pt@gmail.com

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Avenue living

Data Engineer

Jul 2025 – Present · 11 mos · Calgary, AB · On-site

Built an agentic AI solution using Bing Grounding Search to automatically find company websites, extract advisor data, and push it into HubSpot — end-to-end, fully automated
Integrated Azure AI Foundry to call Claude LLM via API, enabling automated intelligent summarization of code and pipeline changes — connected directly to Confluence, creating a fully automated release documentation workflow with zero manual effort
Developed a web scraping agent using Sequentum to capture Canadian rental market data, optimizing for API rate limits and cost efficiency — reduced daily operational costs by 73% (from $150+/day to under $40/day)
Redesigned event-triggered pipelines to batch-process multiple daily file uploads, significantly reducing Azure costs by minimizing redundant trigger activations
Created a centralized pipeline orchestration system for scheduling and managing multiple pipelines in the development environment
Manage CI/CD pipelines and DevOps responsibilities alongside data engineering and automation initiatives

Data EngineeringPython (Programming Language)

Citi

Data Engineer

May 2022 – Jun 2025 · 3 yrs 1 mo · Remote

Designed and deployed end-to-end ETL pipelines on Azure Data Factory, enabling reliable ingestion of structured and semi-structured data across multiple internal and external sources — reducing manual data handling across reporting teams
Built PySpark processing frameworks on Azure Databricks, improving scalability for large-volume datasets and cutting processing time for downstream analytical workloads
Migrated data validation to Azure Functions, enabling automated quality checks that replaced manual monitoring and reduced pipeline failure response time
Implemented data warehouse solutions in Azure Synapse Analytics with schema design, partitioning, and query optimization — directly supporting regulatory reporting and KPI dashboards
Built Star and Snowflake schema models in Synapse to serve BI and regulatory workloads across multiple business units
Automated ADF pipeline orchestration using metadata-driven patterns (Lookup, ForEach, Copy), reducing pipeline build time for new data sources
Designed and optimized PostgreSQL schemas for ingestion workflows, improving analytical query performance through indexing and tuning
Automated infrastructure deployment via Azure DevOps CI/CD and ARM templates, ensuring consistent environments across dev and production

Data EngineeringData Architects