Rohil Thota
Davidson,NC
Summary
Results-driven Software Data Solutions Engineer with over 10 years of experience in building and optimizing data pipelines and analytics. Specializes in designing scalable solutions within the big data ecosystem and Oracle, alongside strong data modeling skills using Erwin. Delivers business-critical analytics and solutions by collaborating effectively with cross-functional teams in complex enterprise environments.
Overview
11
11
years of professional experience
Work History
Software Data Solutions Engineer
Bank of America
09.2022 - Current
- Led the end-to-end architecture of enterprise risk data platforms supporting wholesale and retail domains, enabling scalable batch processing for regulatory reporting, audit, and advanced risk analytics across the organization.
- Delivered enterprise-grade regulatory and risk reporting solutions, including Basel reporting, FRBC submissions, IRR (Interest Rate Risk), and loss forecasting, ensuring compliance with evolving regulatory expectations.
- Defined and enforced enterprise data governance standards, including data quality, lineage, and compliance frameworks (SOX, GDPR/GLBA), driving consistent auditability and reducing regulatory risk across critical data assets.
- Architected a reusable Change Data Capture (CDC) framework (Type 2 SCD) adopted across 100+ dimensional datasets, standardizing historical data tracking and significantly improving consistency of downstream reporting and analytics.
- Established and evangelized a medallion (Bronze/Silver/Gold) data architecture, improving data reliability and usability:
Bronze: Scalable ingestion of raw structured and semi-structured data
Silver: Conformed, validated datasets with enforced data quality and business rules
Gold: Curated, analytics-ready models powering regulatory reports and executive dashboards - Partnered with data stewards, risk managers, and engineering teams to design domain-driven data models spanning wholesale lending, traded products, market risk, and commercial portfolios, aligning technical solutions with business strategy.
- Drove performance optimization initiatives across Spark SQL, Hive, and Oracle/Exadata workloads, improving pipeline efficiency and reducing compute costs through query tuning, partitioning strategies, and workload parallelization.
- Led the design of scalable ETL orchestration and automation using Autosys and Unix-based frameworks, improving reliability, observability, and operational resilience of mission-critical pipelines.
- Built and scaled active metadata and lineage platform for impact analysis, data discovery, and transparency, empowering cross-functional teams with self-service capabilities and fostering trust in data.
- Mentored junior engineers and provided technical leadership across teams, driving adoption of best practices in data modeling, distributed processing, and data platform design.
Software Engineer II
Bank of America
03.2017 - 09.2022
- Re-architected legacy ETL pipelines using Spark and Python, achieving a 40% reduction in processing latency and improving throughput and resource utilization.
- Built and maintained scalable distributed data pipelines using Hive, Impala, and HDFS, enhancing support for high-volume transactional and analytical workloads in production environment.
- Designed and implemented robust observability frameworks (logging, monitoring, alerting), significantly improving failure detection, incident response time, and overall system reliability.
- Improved system resilience by introducing fault-tolerant processing and automated recovery mechanisms, reducing pipeline failures and minimizing operational overhead.
- Migrated legacy data platforms from Netezza to Hadoop and consolidated multiple small clusters into an enterprise data lake, enabling scalable storage, distributed compute, and simplified data access.
- Handled production support and on-call responsibilities for critical data systems, ensuring high availability and reliability of data delivery to downstream services and stakeholders.
Hadoop Consultant
Bank of America
05.2015 - 03.2017
- Designed and deployed scalable Hadoop-based data lake solutions using HDFS, Hive, and MapReduce, enabling distributed storage and processing of large enterprise datasets.
- Migrated legacy data warehouses (Teradata/Netezza/Oracle) to Hadoop ecosystems, enhancing scalability and enabling more cost-effective data processing.
- Optimized Hadoop cluster performance through effective partitioning, bucketing, and resource management (YARN), increasing job efficiency and throughput.
- Built reusable ETL frameworks leveraging Sqoop, Hive, and Oozie to standardize data ingestion and transformation from multiple RDBMS sources into Hadoop.
- Collaborated with infrastructure and platform teams to tune cluster configurations, enhance resource utilization, and ensure stability of shared environments.
- Supported batch processing workflows and scheduling via Oozie, ensuring reliable data delivery and meeting SLAs for downstream analytics and reporting.
Education
Masters in EE -
University Of Missouri Kansas City
01-2014
Bachelor of Technology (B.Tech) -
Gitam University
01-2013
Skills
Apache Spark
- Spark framework
- Scala
- Python
- SQL
- Hadoop Ecosystem
- Hive
- Impala
- HDFS
- Sqoop
- Oozie
- Unix Shell
- Linux/Unix
- Autosys
- Data lineage
- Data quality
- Regulatory compliance
- Agile/Scrum
- Jira
- Git
- CI/CD practices
- Micro Strategy
- Risk analytics
- Financial analysis
- Financial analysis
Timeline
Software Data Solutions Engineer
Bank of America
09.2022 - Current
Software Engineer II
Bank of America
03.2017 - 09.2022
Hadoop Consultant
Bank of America
05.2015 - 03.2017
Masters in EE -
University Of Missouri Kansas City
Bachelor of Technology (B.Tech) -
Gitam University