codetoday.ioData Engineering & Analytics
Real-time lakehouses, BI dashboards, and data pipelines that actually work
The Problem
Broken ELT jobs that no one owns. BI dashboards that disagree with each other. "Just query the database directly" culture. Data teams spending 80% of time on pipeline maintenance.
Our Solution
End-to-end data platform: ingestion (Kafka/Firehose), transformation (dbt), orchestration (Airflow), storage (Redshift Serverless/BigQuery/Snowflake), and BI (Quicksight/Tableau/Metabase). Data contracts and observability built in.
Data that isn't trusted isn't used. We build data platforms that are fast, reliable, and documented — so your analysts stop rebuilding pipelines and start making decisions.
Tools & Technologies
Our Delivery Process
Data Audit
Source mapping, data quality assessment, existing pipeline review
Architecture Design
Medallion lakehouse pattern, SLA definition, cost modelling
Ingestion Layer
Real-time (Kafka/Kinesis) and batch (Glue/Spark) pipelines
Transform & Model
dbt models, data contracts, unit tests, documentation
BI & Self-Serve
Semantic layer, dashboards, training for your analysts
Case Studies
Not hypotheticals. Real projects, real clients, real numbers.
Real-Time IoT Lakehouse — Industrial Client
Industrial IoTSensor data from 10,000 devices landing in S3 with no processing — unusable for real-time decisions.
Kinesis → Glue → Redshift Serverless + Timestream dual-write — real-time and historical in one platform.
1B+ events/day processed. Alert latency under 90 seconds. Query costs down 60% vs old Redshift.
dbt Migration — E-Commerce Analytics
E-CommerceSQL transformation spaghetti across 200+ stored procedures, no documentation, no tests.
Full dbt migration with modular models, tests, documentation site, CI/CD for dbt runs.
Pipeline failures dropped 90%. New analyst onboarding from 2 weeks to 2 days.
Ready to Get Started?
No sales pitch. A 30-minute call to understand your challenge and tell you honestly if we can help.