Skip to main content

Team Introduction

Team Description​

We are the Data Team, dedicated to driving data-driven decision-making and automation across the organization. Our team is divided into three specialized pillars that work in synergy:

Data Engineer (DE)​

Focuses on data integration, pipeline architecture, and building a robust Data Warehouse. They ensure data is accessible, reliable, and ready for analysis.

Business Intelligence (BI)​

Partners with every division to accommodate their data needs. They handle ad-hoc requests and build dashboards to visualize key performance indicators.

Data Analytics (DA)​

Creates advanced data models, insights, and automation. We leverage available data to build predictive models and efficiencies.


Team Correlation & Flow​

We collaborate closely to deliver value:

  • DA to DE: When we build a model or process that needs automation, we document the reproduction steps and pass it to Data Engineering for deployment.
  • DA to BI: We collaborate with BI on complex requests. If a request requires specialized technical tools or advanced modeling, BI passes it to the Data Analytics team.

Team Workflow


Role Description: Data Analytics​

What is Data Analytics? Data Analytics involves creating advanced models, bots, and automated processes by leveraging the Data Warehouse to help the company gain data-driven insights and operational efficiency.

Responsibilities​

  • Building predictive models and advanced analytics solutions.
  • Automating manual processes using data and bots.
  • Providing deep insights to support strategic decisions.

Objectives & Key Results (OKR)​

  • [To be defined]

Tech Stack​

We utilize a modern stack to handle data at scale:

Languages & Frameworks​

  • Python: Primary language (Pandas for transformation, etc.)
  • API: Building interfaces for data apps

Infrastructure & Orchestration​

  • Apache Airflow: Workflow orchestration and scheduling
  • AWS Environment:
    • Redshift: Data Warehouse
    • S3: Data Lake
    • EC2: Virtual Machines

Reporting Tools​

  • Amazon QuickSight: BI and visualization
  • Metabase: Easy exploratory data analysis

Collaboration & communication​

  • Discord: Team chat and alerts
  • Open Project: Task tracking

Data Infrastructure


What We've Done​

We have delivered impactful projects focusing on automation, location intelligence, and operational optimization, including:

  • Location Intelligence: Analyzing customer locations and optimizing Point of Sales (POS) placement based on sociographic and revenue data.
  • Route Optimization: Algorithms to find the most efficient flight and delivery routes.
  • Customer Experience: NLP-driven intent extraction and automated bot replies.
  • Operational Efficiency: Cost tracking and performance bonus systems for partners.

(Note: Specific project details are maintained internally)