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Open to Opportunities · Chicago, IL · Remote / Hybrid

Data Engineer.
Cloud Native.

2+ years building scalable ETL pipelines and cloud-native data architectures across AWS, Azure, and GCP. From real-time wildfire intelligence to NACHA banking lakes — delivering systems that cut errors by 40% and accelerate insights by 60%.

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0%
Pipeline Errors Reduced
0%
Data Prep Time Cut
0%
Faster Execution
0+
Years Enterprise DE

Multi-Cloud Expertise

Three clouds.
One engineer.

Production-grade data engineering across AWS, Azure, and GCP — each chosen for the right job.

🟠

Amazon Web Services

Primary Cloud · Production
S3AWS GlueLambda RedshiftAthenaLake Formation SESCloudWatchCloudFormationFargate
🔵

Microsoft Azure

Databricks · dbt · ADF
DatabricksAzure Data Factory Synapse AnalyticsADLS Gen2 CosmosDBAzure DevOpsAzure Blob
🔷

Google Cloud

BigQuery · Analytics
BigQueryCloud Storage Pub/SubDataprocIAM

Core Toolchain

Orchestration & Processing

Engines behind every pipeline — batch ETL to real-time streaming.

Apache SparkPySparkApache Airflow dbtApache KafkaHadoop TerraformDockerKubernetes JenkinsGitLab CI

Technical Stack

Built to
engineer
at scale.

Every tool chosen intentionally. Every decision made for production reliability.

Languages
PythonSQL PL/SQLScalaR JavaShell / Bash
Data Warehousing
RedshiftBigQuery Azure SynapseCosmosDB PostgreSQLMySQLSQL ServerAthena
Architecture Patterns
Four-Zone Data LakeMedallion Architecture Incremental LoadsEvent-Driven Real-Time IngestionStar Schema
Monitoring & Observability
AWS CloudWatchPrometheus GrafanaSplunkDataDog
Analytics & BI
Power BIAmazon QuickSight DOMOdbt Metrics
Governance & Compliance
SOC 2GDPR Lake FormationRBAC / IAMLineage Tracking

Career

Where I've built.

Real production systems, real impact — across AI disaster response, banking, and enterprise SaaS data.

Data Engineer Intern
Interlinked — AI-Powered Disaster Response Platform
📍 Berkeley, California (Remote) 🏢 AI / Environmental Tech
Mar 2026 – Present
AWSAzure DatabricksPySpark dbtApache Airflow Real-TimeML Pipelines
40%
Latency Reduced
60%
Data Prep Cut
50%
Fewer Incidents
Real-Time
Threat Detection
  • ›
    Engineered real-time wildfire sensor data ingestion pipelines using Apache Spark on Databricks and AWS S3, reducing data availability latency by 40% — enabling earlier threat detection for emergency response teams across active wildfire zones.
  • ›
    Built end-to-end dbt transformation workflows on Azure converting raw geospatial telemetry into analytics-ready risk intelligence models — cutting data preparation time by 60% and accelerating dashboard refresh cycles for disaster coordinators.
  • ›
    Developed automated data quality monitoring frameworks using Python and SQL across mission-critical environmental feeds on AWS, reducing data integrity incidents by 50% and ensuring continuous situational awareness.
  • ›
    Designed and orchestrated feature engineering pipelines using Apache Airflow and PySpark to deliver validated, clean inputs to predictive wildfire spread models — enabling more precise resource allocation recommendations for emergency agencies.
  • ›
    Implemented complex PL/SQL and dbt transformation logic across environmental data models on Azure, producing documented pipelines that streamlined compliance and reporting for disaster response stakeholders.
Data Engineer
Addon Solutions
📍 Gujarat, India 🏢 FinTech / Banking
Nov 2023 – Nov 2024
AWS GlueS3 LambdaPySpark Lake FormationSOC 2GDPR
40%
Parsing Errors Cut
4-Zone
S3 Lake Built
0
Audit Findings
SOC 2
Compliant
  • ›
    Architected a four-zone AWS S3 data lake (Landing → Raw → Trusted → Curated) with AWS Glue crawlers and Athena tables enabling ad-hoc analytics across all ingested datasets at scale.
  • ›
    Engineered ETL pipelines using AWS Glue and Lambda to process NACHA banking transaction files; implemented AWS SES alerts for ingestion and transformation completion events.
  • ›
    Authored PySpark schema standardization scripts for multi-format source files — reducing downstream parsing errors by 40% across all active pipelines in production.
  • ›
    Implemented data governance using AWS Lake Formation with least-privilege RBAC, lineage tracking, and SOC 2 / GDPR compliance controls — achieving zero audit findings.
Data Engineer
N Vision IQ
📍 Gujarat, India 🏢 Enterprise SaaS / Analytics
Nov 2022 – Oct 2023
Apache AirflowRedshift TerraformS3 Multi-Source IngestionIncremental Load
35%
Faster Pipelines
5+
SaaS Sources
3
Envs via Terraform
Zero
Full Refreshes
  • ›
    Built Apache Airflow DAGs for multi-source ingestion (Workday, HubSpot, Zendesk, Kantata, QuickBase) into a unified data warehouse with automated dependency management and retry logic.
  • ›
    Supported warehouse migration to AWS Redshift + S3 + Lake Formation; provisioned all infrastructure via Terraform across dev, staging, and production environments — infrastructure-as-code from day one.
  • ›
    Designed incremental load strategies replacing full-refresh patterns — reducing pipeline execution time by 35% across all production DAGs and drastically cutting compute costs.

Key Projects

Impact by
the numbers.

Every metric below is production-earned, not estimated.

Real-Time · AI · Disaster Response
40%
Wildfire Sensor Real-Time Ingestion Pipeline
Real-time ingestion of wildfire sensor telemetry using Apache Spark on Databricks and AWS S3. Reduced data latency by 40%, enabling earlier threat detection for emergency response teams across active wildfire zones.
Apache SparkDatabricks AWS S3PySparkAirflow
Azure · dbt · Geospatial
60%
Geospatial Telemetry dbt Pipeline
End-to-end dbt workflows on Azure converting raw geospatial telemetry into risk intelligence models — cutting data prep time by 60%.
dbtAzurePL/SQL
AWS · Data Quality
50%
Automated Data Quality Monitoring
Python + SQL automated quality monitoring across mission-critical environmental feeds. Reduced integrity incidents by 50% with proactive alerting.
PythonSQLCloudWatch
AWS · Banking · ETL
4-Zone
AWS NACHA Banking Transaction Lake
Four-zone AWS S3 data lake (Landing→Raw→Trusted→Curated) for NACHA banking transaction files. Glue crawlers, Athena tables, SES alerting, PySpark schema standardization — cutting parsing errors by 40%.
AWS GlueS3 LambdaSESPySpark
AWS · Governance
0
Lake Formation SOC 2 Compliance
Lake Formation with RBAC, lineage tracking, SOC 2 / GDPR controls. Zero audit findings across all production datasets.
Lake FormationSOC 2GDPR
Kafka · Real-Time · AWS
30%
Real-Time SaaS Pipeline on AWS
Kafka + Lambda + Redshift real-time ingestion. Reduced mean issue resolution time by 30% via CloudWatch monitoring and proactive runbooks.
KafkaLambdaRedshift
ML · Feature Engineering · Airflow
↑ Precision
Wildfire Predictive Feature Engineering Pipeline
Orchestrated feature engineering pipelines using Apache Airflow and PySpark to deliver validated, clean inputs to predictive wildfire spread models — enabling more precise resource allocation recommendations for emergency agencies.
AirflowPySpark Feature EngineeringAWS S3
Airflow · Multi-Source
35%
Multi-Source Airflow DAG Orchestration
Airflow DAGs for Workday, HubSpot, Zendesk, Kantata, QuickBase. Incremental loads replaced full-refresh — 35% faster across all production DAGs.
AirflowRedshiftTerraform

Let's Talk

Book a 30-min
intro call.

I'd love to chat about data engineering challenges, open roles, or how I can bring production-grade pipeline expertise to your team. Pick a slot and let's connect.

  • Walk through my technical background & projects
  • Discuss your data engineering challenges
  • Explore how I can add value to your team
  • Available for full-time, contract & consulting
📅 Book on Calendly 📞 Call Directly
30-min Intro Call
with Dhwani Patel · Data Engineer
📅
Monday, Jun 2
10:00 AM – 10:30 AM CST
Available
Tuesday, Jun 3
2:00 PM – 2:30 PM CST
Available
Wednesday, Jun 4
11:00 AM – 11:30 AM CST
Available
Friday, Jun 6
3:00 PM – 3:30 PM CST
Available

Education

Academic foundation.

🎓
M.S in Computer Science
DePaul University
Chicago, IL · January 2025 – December 2026
🏛️
B.S in Computer Application
Silver Oak University
Gujarat, India · August 2021 – June 2024

Let's Connect

Ready to build
something great.

Open to Data Engineer, Analytics Engineer, and ETL Pipeline roles. AWS, Azure, or GCP — let's talk.

pateldhwani805@gmail.com 773-815-2616 · Chicago, IL
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