SAIPAVANKALYAN JAMPURAM
Summary
Results-driven Data Engineer with over 3 years of experience building large-scale, statistical, and production-grade inference pipelines, APIs, and analytics solutions across GCP, AWS, and Azure. Skilled in Spark, Kafka, Apache Beam, and BigQuery, handling up to 5 TB daily. Proven ability to develop and optimize ETL frameworks using Airflow and Dagster. Strong background in machine learning pipeline support, system integration, and code collaboration in multi-developer environments. Exposure to Rust and C++.
Overview
3
3
years of professional experience
Work History
BI Developer Analyst
University of Alabama at Birmingham
01.2024 - 05.2024
- Constructed statistical dashboards utilizing Power BI and Tableau, decreasing reporting time by 30%.
- Integrated real-time Pub/Sub feeds with BigQuery pipelines to enhance data flow.
- Developed APIs and production-ready inference pipelines to strengthen analytics infrastructure.
- Executed BigQuery and SQL queries for data analysis supporting business decision-making.
- Participated in Git-based code collaboration and conducted peer reviews for quality assurance.
Data Engineer
HCL Technologies
08.2021 - 06.2023
- Migrated over 3 million records from SQL Server to Snowflake utilizing Python and SnowSQL.
- Developed PySpark pipelines on Airflow, orchestrating batch and real-time ETL processes with Kafka.
- Built inference pipelines with Spark Streaming to support production machine learning models.
- Enabled high-availability APIs for model outputs through Snowflake integration.
- Deployed CI/CD workflows using Docker, Jenkins, and Kubernetes, reducing deployment time by 60%.
- Created monitoring dashboards via ELK stack, enhancing data validation by 25%.
- Designed Data Lake architecture on AWS S3 and Athena, optimizing Hive queries to cut latency by 50%
Data Engineer Intern
Tiger Analytics
01.2021 - 06.2021
- Developed real-time ingestion pipelines using GCP Pub/Sub, BigQuery, and Apache Beam in Dataflow.
- Migrated legacy Oracle DB to BigQuery, enhancing performance by three times.
- Designed PySpark jobs on Dataproc to process over five terabytes daily, decreasing transformation time by 40 percent.
- Orchestrated batch jobs with Airflow/Composer and created DAGs for automated alerts.
- Supported production-level ML model scoring and anomaly detection pipelines.
- Built APIs and reusable data marts that powered over 10 dashboards in Data Studio
Education
Electrical And Computer Engineering
University of Alabama At Birmingham
Birmingham, AL05-2025
Skills
- Cloud platforms: GCP (BigQuery, DataProc, Composer, Pub/Sub), AWS (S3, Lambda, EC2, EMR), Azure (ADF, ADLS, Databricks, SQL)
- Data engineering: Spark (SQL, MLlib, streaming), PySpark, Hive, Apache Beam, Kafka, Airflow, Dagster, Snowflake, HDFS
- Programming and scripting: Python, Java, Shell (Bash), SQL, Rust (basic), C (basic)
- Databases: PostgreSQL, SQL Server, Oracle, MongoDB, and Cassandra
- CI/CD and DevOps: Docker, Kubernetes, Jenkins, Terraform, Git, and Ansible
- Statistical/ML: Data cleansing, anomaly detection, basic modeling
- Visualization: Tableau, Power BI, and Matplotlib
- Tools: TOAD, SQL Developer, Azure Data Studio, GitHub, Teradata SQL Assistant
Timeline
BI Developer Analyst
University of Alabama at Birmingham
01.2024 - 05.2024
Data Engineer
HCL Technologies
08.2021 - 06.2023
Data Engineer Intern
Tiger Analytics
01.2021 - 06.2021
Electrical And Computer Engineering
University of Alabama At Birmingham
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