Hello there!
Let’s build data pipelines that don’t break at 3 AM.
I don't just clean data. I give it therapy.✌️😎
Designing and building scalable data platforms using Spark, Hadoop, Kafka, and Snowflake. Focusing on reliable, high-throughput data systems that power analytics and real-time decisions.
Building end-to-end ETL/ELT pipelines using Python, PySpark, and SQL. Automating batch and streaming workflows that process terabytes of data reliably.
Exposing clean, well-structured data through REST APIs and internal tools for analysts and stakeholders. Enabling teams to self-serve dashboards, reports, and real-time insights.
Designing cloud-native data architectures on AWS and Azure using EMR, Glue, Snowflake, and S3. Optimizing storage, compute, and data flows for cost, performance, and scalability.
Automating data workflows with CI/CD, Airflow, Terraform, and Kubernetes. Ensuring data pipelines are observable, testable, and easy to deploy across environments.
Building real-time and streaming data systems using Kafka, Kinesis, Spark Streaming, and event-driven architectures. Powering fraud detection, customer insights, and time-sensitive analytics at scale.
1. Built real-time data streaming pipelines using Kafka and microservices, improving marketing analytics by 15% and influencing $800K+ decisions.
2. Designed FastAPI-based data APIs and optimized backend data flows, reducing data and API latency by 30%.
3. Automated cloud data deployments with Azure DevOps, Terraform, Docker, and Kubernetes, reducing release times by 40%.
4. Engineered Hadoop + PySpark pipelines for large-scale data ingestion into Snowflake, improving reporting reliability and predictive analytics.
5. Implemented monitoring and observability for mission-critical data pipelines to maintain 99.9% uptime.
1. Engineered distributed ETL/ELT pipelines using PySpark on AWS EMR, cutting large-scale data processing time by 45%.
2. Built Kafka and RabbitMQ streaming systems for real-time ingestion into analytics and microservices.
3. Automated infrastructure for data workloads with Terraform, Ansible, and Kubernetes, reducing manual environment setup by 60%.
4. Optimized Snowflake schema, warehouses, and queries, reducing compute costs by 30% and improving data reliability by 70%
5. Developed interactive dashboards with Tableau and integrated secure, scalable APIs for frontend apps.
6. Developed and maintained Airflow DAGs for reliable, production-grade data orchestration across cloud environments.
1. Built foundational ETL workflows using Python, PySpark, and Airflow to support fraud analytics and SaaS reporting
2. Containerized data services using Docker and Kubernetes, improving scalability and reducing hosting costs by 20%
3. Developed event-driven data ingestion with Kafka and backend APIs, enabling real-time fraud detection with 10-second latency.
4. Helped design secure database models and JSON/SOAP integrations for large financial datasets
5. Supported CI/CD and infrastructure-as-code practices for analytics and data pipelines on AWS, Azure, and GCP.
Completed advanced coursework in software development, algorithms, database systems, and cybersecurity, with a focus on practical applications in fields such as artificial intelligence, data science, and network security. Developed strong analytical and problem-solving skills for real-world computational challenges.
Gained a strong foundation in software development, networking, database management, and web technologies. Developed practical skills in programming languages, system analysis, and project management. Completed various projects involving web development, data structures, and cybersecurity, preparing for diverse roles in the IT industry.
As a Campus Ambassador during my BTech in Information Technology at Kakatiya University, I undertook various responsibilities:
1. Actively engaged with students and faculty to promote initiatives related to technology and education.
2. Organized events to foster learning and collaboration within the campus community.
3. Built strong networks among students and faculty to enhance communication and engagement.
4. Leveraged digital platforms to effectively disseminate information and resources.
5. Raised awareness about industry trends and opportunities to encourage student involvement.
6. Served as a key liaison between external organizations and the university community, facilitating partnerships and collaborations.
Lokesh is not only a personable and engaging individual but also a highly skilled data engineer. His ability to understand complex data problems, design scalable pipelines, and keep learning new tools in the big data space makes him stand out. I strongly recommend him to any team looking for someone who can own data platforms end-to-end.
Lokesh is approachable, fast-learning, and technically strong in Python, cloud, and data engineering. He has a solid grasp of how to build scalable data systems and automate infrastructure using modern DevOps practices. His curiosity and adaptability make him a great fit for teams building cloud-native data platforms.
Lokesh is more than just a humorous guy, he's an exceptionally skilled and diligent teammate. With a strong focus on results and a deep curiosity for technology, and delivers high-quality solutions in Python, cloud, and data engineering. His passion and enthusiasm for the field truly stand out. I highly recommend Lokesh to anyone looking for a capable and growth-minded developer
Working with Lokesh is always a pleasure. He combines strong skills in Python, cloud platforms, and data engineering with a genuine enthusiasm for solving complex problems. Whether it's building ETL jobs, optimizing SQL, or automating workflows, he takes ownership and delivers. Any data-driven team would be lucky to have him.
I’m always happy to connect, unless you’re a corrupted CSV pretending to be human. Got a data problem? Let’s turn it into a pipeline so clean even your Snowflake bill will smile. Use the form if you trust automation, or message me manually like it’s pre-Airflow 2015. Either way, I’ll pretend I’m not refreshing my inbox every time a Kafka message arrives.
Phone: +1 314 798 2093 Email: lokeshgadesula995@gmail.com
