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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 Gen2
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.

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