You will get I will build scalable ETL pipelines and data engineering solutions
Project details
Build scalable, reliable, and production-ready data engineering solutions tailored to your business needs.
I specialize in designing and implementing ETL/ELT pipelines, data warehouses, cloud-based data platforms, and automated data workflows. Whether you need to migrate data, integrate multiple data sources, optimize existing pipelines, or build a complete analytics-ready architecture, I can help deliver efficient and maintainable solutions.
My expertise includes Azure Data Factory, Azure Databricks, Azure Synapse Analytics, SQL Server, Python, PySpark, AWS Glue, Snowflake, Apache Spark, and modern data engineering best practices.
What you'll receive:
• End-to-end data pipeline development
• Data warehouse design and implementation
• Data integration and migration solutions
• Data quality validation and monitoring
• Performance optimization and tuning
• Documentation and deployment support
• Scalable cloud-based architecture
Every solution is designed with reliability, performance, security, and future scalability in mind.
I specialize in designing and implementing ETL/ELT pipelines, data warehouses, cloud-based data platforms, and automated data workflows. Whether you need to migrate data, integrate multiple data sources, optimize existing pipelines, or build a complete analytics-ready architecture, I can help deliver efficient and maintainable solutions.
My expertise includes Azure Data Factory, Azure Databricks, Azure Synapse Analytics, SQL Server, Python, PySpark, AWS Glue, Snowflake, Apache Spark, and modern data engineering best practices.
What you'll receive:
• End-to-end data pipeline development
• Data warehouse design and implementation
• Data integration and migration solutions
• Data quality validation and monitoring
• Performance optimization and tuning
• Documentation and deployment support
• Scalable cloud-based architecture
Every solution is designed with reliability, performance, security, and future scalability in mind.
Database Type
MySQL, MS SQL, SQLite, PostgreSQL, MongoDB, Azure Cosmos DBWhat's included
| Service Tiers |
Starter
$150
|
Standard
$500
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
Number of Tables Added | 3 | 10 | 25 |
Schema Diagram | |||
Permissions Setup | - | ||
Import/Export Data | |||
Admin Panel Setup | - | - |
Frequently asked questions
About Tejas
Data Engineer - Pipelines, ETL & Scalable Data Systems
Ahmedabad, India - 3:48 am local time
𝐖𝐡𝐚𝐭 𝐈 𝐰𝐨𝐫𝐤 𝐨𝐧:
- Data Pipeline Architecture:- End-to-end pipeline design and development using Apache Airflow, Spark, Kafka and dbt. From raw ingestion to clean, reliable data delivery, built to scale and easy to
maintain.
- ETL & Data Transformation : - Extracting, transforming, and loading data across heterogeneous sources: databases, APIs, flat files, and streaming systems. We make your data consistent, accurate, and ready for analysis.
- Data Warehousing & Storage:- Designing and optimizing data warehouses and lake houses on Snowflake, Big Query, Redshift, and AWS S3. Structured for query performance, cost efficiency and long-term growth.
- Data Quality & Observability:- Automated testing, monitoring, and alerting so you always know your data is trustworthy, before your stakeholders find out it isn't.
Beyond the data layer, my team brings full-stack and backend development
capabilities when a project demands it, so the pipeline we build connects cleanly to
your product without a coordination gap.
𝐇𝐨𝐰 𝐈 𝐰𝐨𝐫𝐤:
I start by understanding your data landscape and business goals before touching a single tool. Then we design, build, test, and hand over infrastructure you own, with documentation and zero ambiguity.
Steps for completing your project
After purchasing the project, send requirements so Tejas can start the project.
Delivery time starts when Tejas receives requirements from you.
Tejas works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements Analysis
Review your business requirements, data sources, existing architecture, and project objectives.
Solution Design
Design the data architecture, ETL/ELT workflow, data model, and implementation approach.