Ravi Retineni Email & Phone Number

San Jose, Ca, Us

• Direct data management, architecture, big data engineering, and a $10M annual budget, leading a team of 95 technical staff across the U.S., India, and China.• Drive data-driven decision-making by defining the vision, strategy, and development of data roadmaps, platforms, and advanced engineering solutions.• Strengthen competitive advantage through data analytics in product development, customer experience, financial crime investigations, fraud risk management, compliance, and payment processing.• Lead cloud migration initiatives for data engineering and analytics applications in risk and compliance management.• Build, train, and mentor a high-performing engineering team, delivering key insights to internal stakeholders.• Architect and deploy near real-time data pipelines, data foundations, and Data Asset Management systems on cloud and on-premises environments.• Holder of 3 patents for innovative data solutions.Key Achievements:• Achieved a 30% increase in operational efficiency through the implementation of a comprehensive data strategy.• Transformed hundreds of legacy data engineering processes with advanced platform capabilities, leading to a 90% reduction in operational costs.• Collaborated with product, finance, and compliance teams to integrate analytics, resulting in a 15% improvement in product launch times and a 20% decrease in compliance issues.• Enhanced customer satisfaction scores by 25% through data analytics.• Decreased financial crime losses by 30% by implementing data engineering solutions and predictive analytics models

San Jose, Ca, Us

• Improved customer loyalty, satisfaction, and service levels while reducing costs by building advanced data analytics capabilities and solutions.• Enabled real-time risk detection by overseeing the architecture, planning, and execution of big data platforms.• Built scaled solutions with streaming and batch data processing platforms on big data and distributed real-time systems.• Developed a robust petabyte-scale data platform to support model simulations on HBase.• Established near real-time data engineering capabilities to minimize customer friction and improve customer experience and service delivery• Hired, trained, and lead 28 data engineering and product managers across the U.S., India, and Tel Aviv.

San Jose, Ca, Us

• Led data architecture and engineering initiatives at eBay Inc. to develop core enterprise data assets supporting analytical use cases for eBay, PayPal, and StubHub.• Managed data architecture and engineering efforts, including data warehousing (Teradata & Hadoop), for payments, user 2.0, risk management, and global customer success applications.• Developed several innovative technologies, including Kafka for near-line data movement, Hadoop for centralized data repositories, HBase for risk detection, Platfora for web analytics, and a combination of Kafka with Storm/Spark for real-time processing.• Executed large-scale, transformative migrations of legacy systems with a well-defined transition strategy, ensuring legacy payment processing technology remained operational for approximately 300 million active accounts.• Recruited, trained, and developed a high-performing engineering team across the U.S., India, China, and Tel Aviv.

Omaha, Nebraska, Us

• Led data engineering, capture strategy, integration, warehousing, analytics, business intelligence, and 20 development staff. • Defined analytical requirements for data architecture, source data analysis, and business intelligence frameworks.• Conducted proofs-of-concept and cost-benefit analysis of the new software, hardware, and staff to build a data warehouse.• Led metadata prototyping by designing IBM information warehouse, data models, and data lakes.• Collaborated with business end-users to capture analytical requirements, program specifications, and SourceToTarget maps.• Saved $3M in costs by deploying predictive analytics and lifetime customer value models, improving marketing campaign effectiveness, delivering campaign management and CRM solutions, and enabling market segmentation strategy.• Enriched customer data with external demographic data and past interactions to increase the lift of cross-sale campaigns.• Integrated Websphere Customer Center and source systems, using Enterprise Service Bus as integration hub.• Led customer data integration between Websphere Customer Center and legacy customer data stored on the mainframe.• Created XML files to enterprise service bus ESB, used XSLT to transform formats, and led data extract, transform, and load (ETL) for several balanced scorecards, rider data mart, data mining, data warehouses, and integration projects.

Edison, New Jersey, Us