Designing Scalable Data Pipelines on GCP for Smart Meters

Designing Scalable Data Pipelines on GCP for Smart MetersDesigning Scalable Data Pipelines on GCP for Smart Meters

The network for creativity

Join 1.25M professional creatives like you

Connect with clients, get discovered, and run your business 100% commission-free

Creatives on Contra have earned over $150M and we are just getting started

Back to feedPost

Axel L. Lifschitz

• 2d

Pipeline Architecture

End-to-end data pipeline built on GCP for the London Smart Meters dataset. Designed the full architecture: ingestion with dlt, orchestration with Kestra, transformation with dbt and Spark, and storage in BigQuery with partitioned and clustered tables for query optimization.

Google BigQuery Data Engineering Web Scraping Business Workflow Automation dbt Python

Sayedani Shaikh

• Apr 4

Title: Lead Management Dashboard — Data Visualization.

Description: Designed a lead management dashboard to visualize and track key sales metrics including lead status, conversion rates, and session sources. Created a sample dataset and built the dashboard to demonstrate how businesses can monitor their pipeline and make data-driven decisions at a glance.

Tools used:Canva (design), Power BI / Tableau (data visualization experience).

Data Analysis Canva Design Canva Data Visualization

Istiak Ahmed Khan

• 2d

looks great,

Tonye Onuoha

pro

• Apr 4

💡 𝗧𝗶𝗽 𝗼𝗳 𝘁𝗵𝗲 𝗗𝗮𝘆 — 𝗗𝗷𝗮𝗻𝗴𝗼

𝗗𝗶𝗱 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄? Using "only()" and "defer()" in Django can significantly reduce query payload when you don’t need every model field.

🔧 "only()" → Load 𝘰𝘯𝘭𝘺 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘧𝘪𝘦𝘭𝘥𝘴 🔧 "defer()" → Load 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘦𝘹𝘤𝘦𝘱𝘵 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘦𝘥 𝘧𝘪𝘦𝘭𝘥𝘴

Why it matters:

- Less data transferred from DB

- Lower memory usage

- Faster responses for large models

Smart field selection = better performance.

#Python #BackendDevelopment #WebDevelopment #PerformanceOptimization

Django backenddeveloper fullstackdeveloper

Istiak Ahmed Khan

• 2d

Great feedbacks

Imaad Mahmood

• Apr 4

Built a full YouTube analytics dashboard in Google Looker Studio using real channel data from Dark Psychology Archive.

The dashboard tracks 6 KPIs — Views (18,582), Watch Time (51.2 hrs), CTR (4.32%), Likes (1,302), Subscribers Gained (105), and Engagement Rate (10.31%). A monthly trend line reveals the growth curve peaking at 4,266 views in November. Content-type breakdown shows Shorts drive 71% of total views. Top performer: Hoovering at 1,232 views with 8.2% CTR.

Built to help content creators make data-driven decisions on what to post, when, and in what format — without exporting CSVs manually.