02 THE BACKBONE

Automated, zero-loss data extraction.

I architect resilient ETL/EL/ELT pipelines utilizing SSIS, Fivetran, Apache Airflow, and custom Python to securely extract raw operational data from your CRMs and ERPs directly into your central data environment.

Audit Your Data Pipelines
The Bottleneck

The Cost of Broken Ingestion

01

You are relying on brittle, hard-coded extraction scripts. When SaaS applications update their APIs, the scripts break, forcing analysts to spend days fixing code instead of analyzing the business.

02

Your data suffers from severe reporting latency. Because your legacy extractions take 12+ hours to process, your executives are making critical strategic decisions based on data that is already two days old.

03

Your analysts are manually exporting CSVs. Without an automated ingestion layer, highly paid talent is functioning as human middleware just to get the data into the warehouse.

Pipeline Orchestration Architecture

DISTRIBUTED SOURCES
SaaS APIs
ON-PREM DB
FLAT FILES
↓
THE EXTRACTION LAYER
SCHEDULED CRON TRIGGERS CHANGE DATA CAPTURE (CDC) ERROR LOGGING & RETRIES

FIVETRAN · SSIS · APACHE AIRFLOW · PYTHON

↓
DATA DESTINATION
DATA WAREHOUSE / LAKEHOUSE
02 THE ENGAGEMENT

Scope & Deliverables

Every pipeline engagement is scoped strictly to your volume and source complexity. No bloat. No guesswork.

Most Common Scope 01

Managed Cloud ELT

  • 2-4 Weeks Delivery Timeline
  • SaaS & Database Connector Setup (Fivetran/Airbyte)
  • Change Data Capture (CDC) Implementation
  • Automated Incremental Syncing
  • Connector Logging & Alert Configuration
Ideal For

Businesses transitioning to the Modern Data Stack who need to rapidly ingest data from standard CRMs, ad platforms, and cloud SQL databases.

02

Custom Legacy Orchestration

  • 4-6 Weeks Delivery Timeline
  • Custom API Pagination via Python/Pandas
  • On-Premise Legacy Database Connections (ODBC/SSIS)
  • Flattened Audit Trail Parsing
  • Complex Error Handling & Retries
Ideal For

Enterprises that require complex extraction from obscure legacy systems, untracked on-premise hardware, or bespoke internal APIs.

Post-Deployment

Operations & Maintenance

Pipelines break when APIs change. My O&M retainers keep your ingestion architecture secure, monitored, and optimized to guarantee daily data freshness.

01

Custom Python/SSIS bug fixes

02

Pipeline sync monitoring

03

Adding new SaaS connectors

04

API token & security updates

Frequently Asked Questions

Why use Fivetran instead of writing custom API scripts? +
Writing custom code to extract data from standard SaaS tools (like Salesforce, Shopify, or HubSpot) is reinventing the wheel. Managed connectors like Fivetran handle API changes and rate limits automatically. I reserve custom Python scripting strictly for bespoke internal tools, complex pagination, or legacy on-premise databases.
What is Change Data Capture (CDC) and why do we need it? +
Instead of extracting your entire 10-million-row database every night (which is slow and severely spikes compute costs), CDC pipelines only extract the specific rows that were created, updated, or deleted that day. It reduces pipeline sync times from hours to seconds.
What happens if an API fails during the night? +
I engineer strict error logging and automated retry loops into the orchestration layer. If a third-party API endpoint is temporarily down, the system will pause, log the error, alert me, and automatically retry the extraction later without losing any data.

What Happens Next?

Your extraction pipelines are automated and your raw operational data is successfully landing in the warehouse. The next move is applying governed dbt logic to turn that raw data into certified executive dashboards.

Explore Semantic Modeling → View BI Dashboards