Aryan Siroya

Data Engineer with 3 years of experience building and optimizing large-scale data processing systems within distributed environments. Strong expertise in Apache Spark, Kafka, SQL, and Python for developing high-performance batch and real time data pipelines and transformation workflows. Experienced in optimizing Spark execution through partitioning strategies, query planning, and performance tuning.

Managed 80+ production datasets with 99.9% SLA adherence, improving pipeline performance by 40%. Skilled in workflow orchestration, data modeling, data ingestion, data cleaning and building reliable, observable data systems with a focus on scalability, cost efficiency, and system reliability.

Software Engineer Developer I (Uber) - Nineleaps (Client: Uber) - Bangalore, India

(2025-04)

• Designed and implemented large-scale data pipelines using Apache Spark, processing 10+ TB/day.
• Optimized Spark workloads by tuning partitioning strategies, execution plans, and handling data skew, improving performance by 40%.
• Assisted in configuring Apache Kafka topics, partitions, and consumer groups to efficiently ingest live event data from diverse sources, ensuring seamless data flow.
• Managed and optimized 80+ production datasets, ensuring 99.9% SLA adherence.
• Built and Designed workflows, managing dependencies, retries, and backfills for reliable pipeline execution.
• Implemented monitoring, logging, and failure handling mechanisms to improve observability and reliability.
• Analyzed data lineage across pipelines to support debugging, impact analysis, and efficient recomputation.
• Developed reusable data workflows and transformation layers to support scalable data consumption.

Member of Technical Staff 3 (Uber) - Nineleaps (Client: Uber) - Bangalore, India

(2024-04 - 2025-03)

• Designed transformation pipelines using Spark and SQL for processing large-scale datasets.
• Reduced compute costs by 30% through workload optimization and improved resource utilization.
• Built intermediate data layers enabling efficient downstream consumption and reduced query latency.
• Implemented data validation, deduplication, and reconciliation frameworks to ensure consistency.
• Automated workflows and pipeline execution, improving system reliability and reducing manual effort.

Data Platform Engineer – uWorc (Uber) - Nineleaps (Client: Uber) - Bangalore, India

(2023-08 - 2024-03)

• Supported ETL orchestration platform managing 200+ workflows in a distributed environment.
• Diagnosed and resolved pipeline failures related to dependencies, schema evolution, and data inconsistencies.
• Performed root cause analysis to ensure reliable pipeline execution and data delivery.
• Improved system reliability through monitoring, logging, and proactive issue resolution.

Data Engineering Intern (Uber Engagement) - Nineleaps - Bangalore, India

(2023-02 - 2023-07)

• Developed Python-based simulations and optimized SQL queries, improving performance by 20%.
• Gained exposure to distributed data processing and ETL pipeline design.

Bachelor of Engineering - Computer Science (Big Data Analytics) - Chandigarh University (2019 - 2023)