Sai Rajesh
Tanikonda
I build scalable data pipelines and cloud platforms that turn raw data into reliable, high-impact systems. Focused on data architecture, ETL development, and performance optimization.
About Me
I'm a data engineer with 4+ years building production pipelines, cloud warehouses, and real-time streaming systems. I've worked across enterprise migrations, ETL platforms, and reporting infrastructure that teams actually rely on.
I hold a Master's in MIS from the University of Houston.
Currently looking for data engineering roles.
Open to relocation.
Projects
SkyStream
Real-time global flight tracking pipeline. Ingests ADS-B telemetry from ~9,000 aircraft every 10 seconds via Kafka → Spark Structured Streaming → Redis, rendered on a GPU-accelerated deck.gl map with sub-5-second end-to-end latency. Includes email landing alerts and 48-hour historical trail queries via TimescaleDB.
Scalable URL Shortener
Cache-first URL shortener engineered for high read throughput. Redis handles the redirect hot path; async background workers flush click counters to PostgreSQL in batches. Real-time analytics UI, one-command Docker Compose deploy.
NYPD Arrests Pipeline
End-to-end analytics pipeline over 500K+ NYPD arrest records (2023–2024). Cleaned with Alteryx, modeled dimensionally, loaded to BigQuery for sub-second aggregations, visualized in an interactive Power BI dashboard by borough, offense type, and demographics.
EV Adoption Analysis
Visual deep-dive into U.S. electric vehicle adoption from 2010–2024. Analyzes charging infrastructure gaps, state-by-state adoption rates, and federal policy impact — from 200K EVs in 2013 to over 4 million by 2024.
DIY CNC Plotter
2-axis CNC plotting machine built with Arduino UNO + GRBL firmware, 3D-printed components, and NEMA 17 stepper motors. Extended with an ESP32 IoT layer for wireless G-code transmission, browser-based control, and real-time telemetry.
Experience
- →Designed and maintained operational reporting pipelines powering day-to-day program decisions across departments.
- →Built and managed data infrastructure connecting disparate source systems into a unified reporting layer.
- →Collaborated with stakeholders to translate business requirements into reliable, repeatable data products.
- →Led Salesforce-to-AWS migration, redesigning data flows to reduce sync latency and improve reliability across downstream consumers.
- →Built real-time Kafka ingestion pipelines handling high-throughput event streams from multiple production systems.
- →Developed dbt transformation layers and Spark processing jobs for analytics-ready datasets in Redshift.
- →Built SQL-based reporting across operational databases serving finance and operations teams.
- →Maintained ETL processes, dashboards, and ad-hoc analyses supporting executive decision-making.
Blog Posts
Deep dives into the systems I build — the architecture, the decisions, and what I learned.
Every layer of the system: Kafka checkpoint gotchas that blanked the map, why Redis writes must precede Postgres, how deck.gl handles 9,000+ GPU-accelerated points, and the four production bugs I actually hit.
Read Post →How cache-first architecture and async click tracking combine to build a URL shortener that stays fast under heavy read load — without sacrificing analytics accuracy.
Read Post →Profiling, cleaning, and modeling 500K+ arrest records into an interactive Power BI dashboard that surfaces borough-level crime patterns and demographic trends.
Read Post →From 200K EVs in 2013 to over 4 million by 2024 — a state-by-state breakdown of adoption rates, charging infrastructure gaps, and the policy drivers behind the transition.
Read Post →Contact
I'm actively looking for data engineering roles where I can work on high-throughput streaming systems, large-scale data infrastructure, and the tooling that makes data reliable at scale.