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David Renda
Extract
✔︎
Transform
✔︎
Load
✔︎
Running pipeline: [ job_title ]
Building solutions to keep your data fast and your business too.
About Me
Hi! I'm David, a data architect with a full-stack background spanning networking, cloud infrastructure, and end-to-end data pipelines. I started my career hands-on with LAN/WAN design and server deployments, gradually evolving into cloud infrastructure and data-driven projects. Over the years, I've built robust ETL/ELT pipelines, migrated legacy systems to modern cloud architectures, and enabled data-informed decision-making across organizations. I'm passionate about MLOps and AI/ML workflows, experimenting with model deployment, automation, and workflow orchestration. I also run The Data Mothership, a weekly newsletter where I share insights and experiments in data architecture design, engineering and analytics.

Languages

  • English
  • French — A2

Programming Languages

  • Python
  • SQL
  • Bash/Shell

Expertise

  • ETL/ELT pipeline design
  • Data Modeling
  • Workflow Orchestration
  • Data Warehousing design
  • Git & Version Control

Tools

  • Azure Data Factory
  • Data Bricks
  • Power Query/Data Flows
  • Azure Data Lake Storage
  • Power BI
  • dbt
  • Mulesoft
  • Snowflake
  • Tableau
Recent Projects

Job Market Data Pipeline

Problem: Job boards are intermediaries. Companies post to their ATS first, then it gets syndicated days later.

Solution: Built automated ETL pipeline scraping 5,400+ jobs directly from Greenhouse APIs every 3 hours, bypassing job boards entirely.

Impact: See opportunities 2-7 days before competitors on LinkedIn/Indeed. Interactive dashboard with real-time filtering, search, and application tracking.

Tech: Python (requests, pandas), HTML/CSS/JavaScript, Git, Windows Task Scheduler

View Dashboard →

Cloud Reporting Modernization

Problem: Legacy SSRS reports were slow, difficult to maintain, and disconnected from modern cloud data infrastructure.

Solution: Architected and migrated to cloud analytics stack using Azure Synapse, ADLS, and Power BI, redesigning data models and modernizing reporting layer.

Impact: 60% faster query performance, improved data governance, enabled self-service analytics for 50+ business users, reduced maintenance overhead by 40%.

Tech: Azure Synapse, ADLS, Power BI, dbt, T-SQL, Git

CRM Cloud Transformation

Problem: On-premises CRM system was expensive to maintain, inflexible, and unable to scale with business growth.

Solution: Led migration of legacy CRM to Dynamics 365, designed Azure Data Factory ETL pipelines, and modernized workflows and reporting with Power BI.

Impact: Reduced infrastructure costs by 35%, improved user adoption through modern UI, enabled real-time reporting across 200+ users, accelerated business processes.

Tech: Azure Data Factory, Dynamics 365, Power BI, Azure SQL, Python

Secure FTP Data Pipeline

Problem: Manual FTP data transfers between external partners were error-prone, insecure, and lacked audit trails for compliance.

Solution: Architected secure, automated Azure solution using Data Lake Storage and Data Explorer to streamline encrypted data flows with full governance and access controls.

Impact: Eliminated manual errors, enabled 24/7 automated data ingestion, achieved compliance with data retention requirements, improved partner integration speed by 80%.

Tech: Azure Data Lake Storage, Data Explorer, Managed Identities, VNETs, Python

Experience

Data Architect

2022 — Present

California Department of Community Services and Development

  • Led end-to-end modernization of Dynamics CRM analytics platform, implementing Synapse Link → ADLS → Synapse Pipelines → dbt → embedded Power BI, replacing legacy SSRS architecture.
  • Designed and operated scalable ELT frameworks in Azure (ADF, Synapse, Databricks) supporting high-volume transactional and event-based data workloads.
  • Architected secure data platform integrations using VNETs, private endpoints, managed identities, and RBAC to enforce governance and compliance.
  • Established modular dbt modeling standards to improve transformation reliability, maintainability, and cross-team development velocity.
  • Implemented monitoring and observability using Azure Monitor and Log Analytics to enforce data freshness, latency, and reliability SLAs.
  • Partnered with application, analytics, and product teams to embed analytics directly into enterprise workflows

Data Engineer

2017 — 2022

AH Parts

  • Designed, deployed, and maintained LAN/WAN networks and virtualized server environments, building a foundation for reliable data operations.
  • Managed Active Directory, user permissions, storage solutions, and virtual servers, ensuring structured access and governance of operational and business-critical data.
  • Implemented automated scripts to streamline server maintenance, backups, and monitoring, reducing manual intervention and preparing datasets for reporting and analytics.
  • Monitored system performance and network traffic, identifying bottlenecks and ensuring high availability for both operational and emerging data pipelines.
  • Collaborated with security and IT teams to enforce compliance, firewall rules, and access controls, securing sensitive data while supporting analytics initiatives.
  • Documented systems, workflows, and operational procedures, creating reusable references for both infrastructure and early-stage data projects.
  • Supported early cloud adoption and hybrid deployments, preparing on-premises infrastructure for integration with cloud-based data storage and processing solutions.
  • Participated in data-related projects, including automating data extraction from operational systems and integrating datasets to support reporting and analytics.
  • Developed ownership of end-to-end data movement workflows, gaining experience in ETL concepts, data validation, and pipeline reliability even before formally becoming a data engineer.

Contact

Have a project in mind or want to connect?

Email: David_Renda@yahoo.com

LinkedIn: View Profile

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