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athithyaraagul.com
DWG–00 · ElevationScale NTS
Data Engineer — Chennai, India

Systems that
move data.

I design data pipeline architecture across Google Cloud and Azure— built to move data reliably, recover from failure, and run unattended. Python, SQL, and Docker underneath every layer.

Pipelines
10 shipped
Clouds
GCP + Azure
Cert.
DP–900
INGESTEVENTS / CDCSOURCESPARK / SQLTRANSFORMWAREHOUSESINK

Sheet 01

The
Work

Six flagship builds — streaming and batch, cloud and on-prem. Full write-ups and source on GitHub.

DWG-01Azure

Azure Audit Pipeline

End-to-end audit pipeline that lands infrastructure and security telemetry, transforms it in Data Factory, and serves it from Synapse serverless SQL.

Logs→Data Factory→Synapse

Source
DWG-02Real-time

CDC Streaming Pipeline

Event-driven Change Data Capture that keeps a target store synced row-for-row with its source as changes happen, no batch window required.

Source DB→Stream→Target

Source
DWG-03Warehouse

SQL SCD2 Warehouse

Slowly Changing Dimension Type 2 modeling that preserves complete row history through pure SQL transformations — no external CDC tooling.

Source→SQL→SCD2 Target

Source
DWG-04Lakehouse

Local Medallion Lakehouse

A self-hosted bronze/silver/gold lakehouse — raw landing, cleaned and conformed tables, then business-level marts — built to prove the medallion pattern without a managed platform underneath it.

Bronze→Silver→Gold

Source
DWG-05AI / ML

TriFusion AgroVision

Agricultural computer-vision model fusing three inputs into a single classifier, reaching 99.28% accuracy and a 0.993 macro-F1 on held-out data.

Imagery→TriFusion Model→Classification

Source
DWG-06Analytics

F1 Telemetry Dashboard

Interactive dashboard parsing high-resolution Formula 1 telemetry into driver-level metrics — lap deltas, sector pace, and tyre degradation.

FastF1 API→Python→Dashboard

Source

Sheet 02

Drawing
Register

Four more pipelines on file — smaller in scope, still shipped and documented.

DWG-07Streaming ETL PipelineGCP · Real-timeDWG-08Airflow + Dataproc ServerlessGCP · BatchDWG-09Hadoop Incremental PipelineOn-prem · DistributedDWG-10Observability StackDevOps · Monitoring

Sheet 03

Bill of
Materials

Every component listed by group — picked for the job, not the logo.

01

Languages

PythonSQLBash
02

Google Cloud

DataflowBigQueryPub/SubDataprocCloud ComposerGCS
03

Microsoft Azure

Data FactorySynapseDatabricksADLS Gen2Azure OpenAI
04

Processing & Storage

PySparkApache BeamDelta LakeMedallionHadoop / Hive
05

Orchestration & Ops

AirflowDockerGitHub ActionsPrometheusGrafana
06

Analytics & BI

Power BIFastF1SageMaker
DP-900 CertifiedMicrosoft Azure Data Fundamentals

Sheet 04

Revision
Log

Where the work has run so far.

REV A
Jun — Jul 2023
Completed

Data Analyst Intern

Corporate Gurukul — in collaboration with the National University of Singapore & AWS

  • Ran exploratory analysis on large datasets in an Agile team to surface high-impact ML opportunities aligned with product goals.
  • Built and deployed ML models on AWS SageMaker, validating above 90% accuracy in a production-oriented environment.
  • Translated technical findings for stakeholders, keeping engineering work tied to business objectives.

Title Block

Let’s
build.

athithyaraagul05@gmail.com
GitHubLinkedIn
Drawn By
Athithyaraagul S.
Location
Chennai, India
Role
Data Engineer
Status
Open to work