Sivaprasad Pandeti
Sr Bigdata Architect @Nike
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WORK HISTORY
Sr Bigdata Architect @Nike
Portland, OR, US
Member of campaign team that is building a holistic view of the Nike consumer journey through data and analytics and syndicating key trends and KPI\'s to inform the development of global digital services and consumer experiences ranging from email to online and mobile apps to physical in-store moments.• Developed data pipelines using spark and hive for Campaign team that loads the response generated from the emails and app activity of the customers of Nike to analyze the trends and effectiveness of the campaigns that have sent out to the customers.• Source date, curate and syndicate KPI’s from multiple consumer touchpoints ranging from email campaigns, mobile fitness apps (NRC + NTC), online and mobile shopping experiences (Nike.com, SNKRS and Nike App) and brick and mortar consumer offerings.• Coordinated with Data science team to come up with new business requirements and implemented them on the Data pipelines.• Worked on Airflow workflows for scheduling the hive and spark jobs.• participated in design solution brain storm sessions to create standard framework to be developed to capture the metrics of the spark loads to redshift and do the data quality check and subsequently start or stop the subsequent jobs in order to maintain the data correctness and reducing the customer complaints.• Defined standards, best practices and design patterns to make the applications efficient, scalable and easily maintainable.• Built scripts and utilities for automating and streamlining many processes and written optimized HQL’s jobs.• Expert in analyzing complex problems and identifying root cause and providing solutions
EDUCATION
Jawaharlal Nehru Technological University
Bachelor of Technology (BTech), Computer Science
SKILLS
ABOUT SIVAPRASAD PANDETI
Proven Data Engineering Manager with 15+ years experience leading cross-functional teams, scaling distributed systems, and delivering multi-million-dollar data products. Expert in system architecture, people management and agile execution. Proven record of building and managing high-performing teams and improving engineering velocity by 30–50%.Expert in building data engineering teams, designing robust ingestion and transformation frameworks, stabilizing mission-critical pipelines, and delivering analytics solutions.• Hired and Mentored 20 data engineers spread across 3 teams, improving technical skills and productivity thus decreasing delivery time by 25% and Improved system throughput by 40% and reduced operational incidents by 60% and delivering 100% of high-priority features before schedule exceeding users satisfaction levels.• Relentless focus on creating engineering best practices and workshops with the teams that help them to come up with best templates for code reviews, CI/CD, documentation standards, on-call coverage, and operational run-books to combine with agile execution processes that improved sprint predictability, team velocity.• Expertise in system solution architecture and design in Databricks, Apache Spark, Airflow, AWS (S3, EMR, Lambda, Redshift, Glue), Azure, LLM’s, Gen AI, Snowflake, SQL, Python, CI/CD, Docker, Data Modeling, Distributed Systems, ETL/ELT • Improved inbound/outbound shipment forecasting accuracy by 20–40%.Enabled distribution centers to track dock-to-stock cycles, labor utilization, picking/packing efficiency, and outbound shipment performance.Provided insights that helped reduce bottlenecks and optimize labor planning across multiple DCs.Skills:• Data warehousing • Business Intelligence • Big Data • SDLC methodologies • Working with Executives and Customers • Relationship building • Project management • People management • Leadership • Entrepreneurship • Hadoop • Hive • HBase • Pig • Sqoop • Cascading • Lingual • Flume • Spark • Amazon Web Services • Abinitio • Informatica • SQL • Oracle • Teradata • Business Objects • Talend • Autosys • Unix shell scripting • Python • HTML • CSS • JavaScript • C • Java • Scala
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