☁
Ravi Teja
Data Engineer
Download CV → Book a Meeting
DATA ENGINEER | MICROSOFT AZURE · PYTHON · SQL

I Engineer Data
That Moves.

5+ years' combined experience across data engineering and data testing, specialising in Microsoft Azure, Python, SQL and end-to-end ETL/ELT pipeline delivery — from raw ingestion to trusted, production-ready platforms.

View My Projects → ↓ Download CV 🗓 Book a Meeting
Python SQL PySpark Azure Databricks Fabric
From Raw Data → To Business Insight
☁
API
→
⚙
Ingestion
→
🗄
Bronze
→
🗄
Silver
→
🗄
Gold
→
🏠
Warehouse
→
📊
BI

My Data Engineering Journey

From diverse data sources to trusted insights — building the pipelines that power decisions.

☁

DATA SOURCES

APIs · Files · Databases
Events · Streaming
→
⚙

INGESTION

Azure Data Factory
Python · APIs
→
✦

PROCESSING

Databricks · PySpark
Spark
→
🗄

DATA LAKE

ADLS Gen2 · Delta Lake
SCD1 / SCD2
→
🏠

WAREHOUSE

Synapse · SQL
Microsoft Fabric
→
📊

CONSUMPTION

Power BI · Analytics
Applications

Technical Arsenal

The tools and technologies I use to build, manage and scale data platforms.

🐍

Programming

  • Python (Pandas, PySpark)
  • Requests, JSON, Pathlib
  • Azure SDK
  • SQL & T-SQL
△

Azure & Cloud

  • Azure Data Factory
  • Data Lake Storage
  • Blob Storage
  • Azure SQL Database
  • Synapse Analytics
  • Key Vault · Monitor
  • Databricks · Azure DevOps
🗄

Data Engineering

  • ETL / ELT
  • Data Integration & Transformation
  • Data Cleansing
  • Data Validation & Quality
  • Data Modelling & Warehousing
  • Batch Processing
  • API Integration
◈

Testing & QA

  • Data & ETL Testing
  • Source-to-Target Validation
  • Data Reconciliation
  • Regression & Functional Testing
  • Defect Management
  • Databricks Validation Frameworks
◎

Formats & Tools

  • CSV, JSON, Parquet
  • Git · Azure DevOps
  • VS Code · Jupyter Notebook
  • Power BI

Featured Project

Employee Data Modernisation — Scalable Data Platform

Employee Data Modernisation
Scalable Data Platform
Built an end-to-end data pipeline to ingest employee data from REST APIs, transform and model using Databricks, and load to a data warehouse for analytics.
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ProblemInconsistent data, manual processes, no single source of truth.
⚙
SolutionAutomated pipeline with data validation, SCD1/SCD2 and orchestration.
↑
ImpactImproved data quality, reduced processing time and enabled real-time reporting.
View Details ⌥ View on GitHub
REST API
→
Python / ADF
→
Azure Data Lake
→
Databricks
→
Bronze (Raw)
Silver SCD1 (Updates)
Silver SCD2 (History)
→
SQL / Fabric
→
Power BI
TECHNOLOGIES
PythonADFADLS Gen2DatabricksSQLFabric
KEY FEATURES
✓SCD1 / SCD2
✓Data Validation
✓Incremental Load
✓Monitoring & Logging

Experience Timeline

My journey in data, from analysis to engineering.

2017 – 2020
BSc Computer Science & Mathematics
Loyola
Foundations in programming, data structures & statistics
Jun 2020 – Nov 2021
Data Tester
London, UK
▸Source-to-target validation, SQL
▸Reconciliation · Defect management (Azure DevOps)
Dec 2021 – Present
Data Engineer
London, UK
▸Azure Data Factory · Databricks · PySpark
▸ETL/ELT, data quality & pipeline monitoring

Engineering Principles

How I build reliable, scalable and maintainable data systems.

🛡
Reliable
before fast
⚙
Automated
before manual
◎
Observable
before production
📈
Scalable
by design
✓
Data quality
is part of the pipeline

GitHub Activity

Consistent contributions to open source and personal projects.
24
REPOSITORIES
1,240+
COMMITS
12
FOLLOWERS
TOP LANGUAGES
Python
38%
SQL
22%
PySpark
16%
JavaScript
8%
Other
16%
Last 6 months

Let's Work Together

I'm open to new opportunities and would love to discuss how I can add value to your team.
👤
✉
🏢
💬
🗓 Or book a meeting directly — calendly.com/data96561 ↗