You will get a fast and efficient data engineering ETL/ ELT pipeline
Rising Talent
Rising Talent
Project details
As a specialized data engineer, I deliver cutting-edge solutions tailored to the evolving needs of modern businesses. From scalable ETL pipelines and real-time data streaming architectures to data lakehouse designs, I provide end-to-end expertise in building hybrid data platforms that combine the best of data lakes and warehouses.
Using tools like Apache Spark, Delta Lake, Snowflake, and Kafka, I excel in designing distributed systems, optimizing cloud-native workflows, and ensuring low-latency processing for both batch and streaming data. My solutions include data governance frameworks, schema evolution, and CI/CD-enabled fault-tolerant pipelines to maintain seamless, production-ready operations.
I am ready to support you with high-performance analytics, AI pipelines, and scalable growth. Give me a buzz !
Using tools like Apache Spark, Delta Lake, Snowflake, and Kafka, I excel in designing distributed systems, optimizing cloud-native workflows, and ensuring low-latency processing for both batch and streaming data. My solutions include data governance frameworks, schema evolution, and CI/CD-enabled fault-tolerant pipelines to maintain seamless, production-ready operations.
I am ready to support you with high-performance analytics, AI pipelines, and scalable growth. Give me a buzz !
What's included
| Service Tiers |
Starter
$150
|
Standard
$220
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 2 days |
Number of Revisions | 2 | 3 | 4 |
Source Code |
Frequently asked questions
About Mahmood
Data Engineer, Machine Learning, Deep Learning and Gen AI Developer
Dhaka, Bangladesh - 1:07 am local time
# What I Offer:
Data Engineering Expertise
- Design and implement scalable ETL/ELT pipelines for batch and real-time data processing.
- Build hybrid data lakehouse architectures using tools like Apache Spark, Delta Lake, and Snowflake.
- Enable seamless data integration across diverse sources with a focus on performance and reliability.
- Implement data governance frameworks and ensure robust schema evolution and quality checks.
Big Data & Analytics
- Process and analyze large datasets using advanced tools and frameworks.
- Perform data wrangling, statistical analysis, and predictive modeling to uncover actionable insights.
- Develop high-performance dashboards and reports for informed decision-making.
AI & Machine Learning Development
- Craft bespoke ML/DL models for regression, classification, NLP, and computer vision tasks.
- Build and deploy Generative AI solutions, including fine-tuned Large Language Models (LLMs) like GPT and LLaMA, for chatbots, content creation, and automation.
- Design Agentic AI systems leveraging reinforcement learning for decision-making applications.
- Ensure production-grade deployments optimized for scalability, latency, and seamless integration.
# Why Choose Me?
- End-to-End Expertise: From data engineering to advanced AI development, I deliver holistic solutions tailored to your unique needs.
- Industry-Grade Tools: Proficient in industry-leading platforms and frameworks like **Apache Spark, TensorFlow, PyTorch, Kafka, and Azure
- Results-Driven: My solutions are designed to enhance operational efficiency, unlock new revenue streams, and provide measurable business outcomes.
- Client-Centric Approach: I prioritize clear communication, transparency, and delivering on time, every time.
Ready to transform your data into powerful insights and intelligent systems? Let’s collaborate!
Steps for completing your project
After purchasing the project, send requirements so Mahmood can start the project.
Delivery time starts when Mahmood receives requirements from you.
Mahmood works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis & Architecture Design
Conduct an in-depth discussion to understand project requirements, data sources, processing needs, and end goals. Design a high-level architecture for the pipeline, detailing components like ingestion, transformation, storage, and output layers.
Source Integration & Data Ingestion
Connect to data sources using technologies such as Kafka, REST APIs, JDBC, or cloud-native connectors. Implement scalable ingestion pipelines using Apache Spark or Apache Nifi for batch data and Kafka or AWS Kinesis for streaming data.