Principal Data Engineer
Data Engineer
Available for hire
Years of
experience
9+ years
Experience
level
Principal
Available
for
Full-time, Part-time, Contract, Freelance
Available from
23 Jun 2026
With over 9+ years of experience in designing, building, and optimizing data platforms, data warehouses, and ETL pipelines. Extensive experience working with Apache Kafka, Apache Nifi, Spark, Airflow, ELK Stack, Docker, Kubernetes, and cloud platforms including AWS, GCP, and Azure. Strong experience with modern cloud warehousing solutions including Snowflake, Redshift, and BigQuery, along with dbt for transformation and Azure Data Factory for scalable data integration. Expertise includes leading large-scale data integration and warehousing projects for global organizations, focusing on creating scalable and reliable data solutions. Proven track record in Python-based automation, data architecture, and real-time streaming pipelines, driving improvements in data processing efficiency to support informed decision-making. Experienced in leading and mentoring cross-functional teams to deliver actionable insights and drive data-driven decision-making.
Skills
JavaScript
TensorFlow
SQL
Kafka
Elasticsearch
GraphQL
AWS
Azure
OpenShift
GCP
NoSQL
REST
Lambda
Kubernetes
Supabase
jQuery
MongoDB
PostgreSQL
MySQL
Firebase
EKS
Git
GitHub
CI/CD
Kanban
HTML
Python
Bash
MS SQL Server
BigQuery
Snowflake
Clickhouse
Oracle
Flask
Django
FastAPI
NumPy
Pandas
Apache Kafka
PyTorch
Keras
Apache Spark
Airflow
Languages
Employment History
Principal Data Engineer at
MicroDev Solutions
Current
2022
-
Now
• Led a team of 5 data engineers designing and maintaining enterprise-scale ETL/ELT pipelines using Databricks
and cloud data infrastructure across AWS and Azure.
• Engineered containerized, Docker- and Kubernetes-based data pipelines using Kafka, Python microservices,
and REST APIs, reducing processing time by 40%.
• Designed a scalable, high-performance data architecture supporting real-time analytics across 10+ business
units, incorporating cloud data warehousing solutions such as Snowflake, Redshift, and BigQuery.
• Built and optimized ELT pipelines leveraging dbt and Azure Data Factory to support scalable and maintainable
data transformation workflows.
• Optimized SQL and Bash scripting for automated data ingestion, transformation, and workflow orchestration.
• Managed Git-based CI/CD pipelines for version control and automated deployment of data pipelines.
• Standardized logging and audit frameworks for ETL processes, enabling faster troubleshooting and root-cause
analysis.
• Collaborated with architecture leadership to define governance, lineage, and access frameworks using Unity
Catalog and schema registry.
• Tech Stack / Tools: Apache Kafka, Airflow, Nifi, Python, SQL, Bash scripting, Docker, Kubernetes, Azure Cloud,
REST APIs, Linux
Senior Data Engineer at
TechnoGenics SMC
2021
-
2022
• Designed and optimized large-scale ETL/ELT pipelines using Spark and Airflow to process billions of retail and
consumer data records.
• Migrated legacy Teradata and Oracle systems to Snowflake and AWS S3, cutting costs by 40% and improving
performance.
• Integrated processed datasets into Amazon Redshift to support real-time business intelligence and reporting
needs.
• Created Power BI dashboards to track key KPIs and provide actionable insights for business stakeholders.
• Implemented data validation, monitoring, and lineage tracking to ensure data consistency and governance
compliance.
• Used Git for version control and deployed pipelines via automated CI/CD workflows to ensure reliability and
maintainability.
• Collaborated with cross-functional teams to improve data accessibility, reliability, and overall data engineering
best practices.
• Tech Stack / Tools: Apache Kafka, Airflow, Spark, Python (ETL & automation), SQL, Bash scripting, AWS (S3,
Athena, EMR, Redshift), Snowflake, Power BI, Git, CI/CD pipelines
Software Engineer at
Ebryx Pvt. Ltd
2017
-
2021
• Modernized legacy ETL pipelines and data warehouse workflows, achieving a 30% improvement in processing
speed.
• Implemented Python, Kafka, Elasticsearch, FluentD, and GCP (GKE) solutions, supporting 5+ TB daily data
ingestion.
• Assisted in migration from on-prem Oracle systems to AWS Redshift improving scalability and reporting
performance.
• Achieved a 30% improvement in data processing speed by designing and implementing a robust data
warehouse and ETL pipelines that consolidated data from multiple sources.
• Designed and implemented Star Schema data models for internal reporting, improving query performance and
simplifying business analytics.
• Created ELK-based logging pipelines to capture operational metrics and generate audit-ready reports for
internal teams.
• Created lightweight data lineage maps to help stakeholders trace data flow from source to report.
• Tech Stack / Tools: Python, Apache Kafka, Elasticsearch, FluentD, GCP (GKE, Cloud Storage), Docker,
Kubernetes, SQL, Linux, ELK Stack
Education
MS in Data Science for Business at
University of Stirling
2023
-
2024
BS in Computer Science at
FAST, National University
2013
-
2017