Software Engineering Manager, Adtech OptimizationsLeading a team of 13 engineers that are responsible for Adtech’s Channel Optimization Platform and Location(Point of interests) insights platform. Both Platforms support Intelligent data and optimization products and are leveraged by all of Uber’s marketing managers, 3 cross-functional marketing engineering teams. The Tech stack used was Python, PyML, Hive, Presto, Java, Cadence, Kafka, My SQL, S3, Lucene, REST, Spark.Built the Adtech team and then Adtech’s Channel Optimization team from the ground up. Created a team charter to improve marketing Return on Ad Spend (RoAS) by channel niche optimization algorithms and machine learning models. Established a vision for efficient spend and formed a dedicated team for Adtech Channel Optimization Platform owning all marketing-related optimizations. This platform fuels all of the paid marketing money for Uber and is the decision making engine controlling how much to spend on which campaigns and which markets.Managed and Lead a team of 8 engineers virtually split across different Orgs and built City Pulse supported by Location Insights Platform. Architected the system to handle backend search requests and supporting locations data behind it. It is a miniature version of tripadviser but for popular places that people take uber rides to or order food from. Communicated and aligned leaders around vision across 3 orgs by partnering with 6 teams for correctly architecting this platform. Which was built to be used by all of uber’s web teams as well as marketing teams to serve Points of Interests search requests.

Directed technological planning and Lead enterprise level projects by prioritizing technology initiatives and coordinating the evaluation, deployment, and management of current and future techstack like SSIS vs hadoop eco system + Airflow. Accomplished many milestones that enabled ingestion, integration and hosting of organizational data and created a trusted single source of truth for other systems to consume. Tech stack used was HDP echo systems, REST, .Net, Shell scripting, Python, Hive, Presto, MS sql server, SSIS, SSRS, OLAP* Cloud Cube build performance (Lead Software Dev Engineer – Data Transformations): Lead a team of 4 members. Trained the team on Hadoop Echo systems, Delivered KPIs to measure how smoothly Rackspace hosts are built. Consumed JSON formatted Events generated via Open stack notifications through API and implemented huge datasets in Hive on HDP platform by writing custom SSIS components and .net modules to port hive dataset into SSAS for creating an OLAP cube. Data sources were RDBMS, APIs, Events, notifications, logs.* REST API and JSON Parser SSIS Component (Lead Software Dev Engineer, International BI): Consuming data from rest api was not possible through ETL infrastructure. Architected and implemented reusable ETL components using c# and T-SQL in SSIS which made it possible with just a few configuration parameters. Adopted by the entire company’s data team (60 data engineers).

Supply chain analytics for IPC (InventoryPlanning and Control)o Enable Adhoc analytics on Big data for business users by providing modeled , aggregated data in database , S3 , Redshifto Pick up an undefined vague business problem and gather data and define and prove it by analytics so that it can be solved by building software solutions.o Specifically working closely with Product Managers to define metrics to gauge project success as well as creating operational metrics to track on going operational performance.o Own the design, development, and maintenance of Data models, metrics, reports, analyses, dashboards, etc. to drive key business decisions.

The BI team in amazon provides the enterprise Data Warehouse and analytics platform to approximately 2000+ internal and external customers which is considered one of the world's largest data warehouses. Key responsibilities are to develop the core BI platform technologies that drive all of Amazon's business decisions. The team provides reporting, analysis, data mining, and data integration to all internal and external customers worldwide. This technology serves as a foundation for mining data from Amazon.com Business Intelligence databases and drives business critical decisions at all levels of Amazon.com. Responsibilities also include developing various reports using OBIEE to analyze the business performance, trends over time and ad-hoc reports that enable the business analysts/management to take business decisions. These reports are widely used by 500 plus users from Sales, Marketing and Sales Finance Organizations across the globe.

Operations data mart for Amazon enterprise data warehouseo Develop, enhance and maintain an end-to-end solution for Data warehouse Operations. o Capture, maintain, and report all the required metrics to measure Amazon enterprise Data warehouse performance, growth, health, usage, popularity and much more. o Extend Amazon DW to incorporate rapidly changing Amazon business and growth.o Extend Amazon DW to handle new upcoming technologies.o Cater to the user base of more than 4000 people. o Answer all customers’ query related to DW/BI product or the data warehouse. o This includes, helping them with generating reports, clearing their doubts or making them understand a particular subject area. o Expand, maintain, improve and support Amazon’s enterprise wide data warehouse .Which is one of the biggest data warehouse (~100 terabytes) in the world. o Responsibilities include active monitoring, automations, enhancing existing subject areas and tuning the transform and load processes to handle high volumes and meet SLA. o Manage, maintain and expand the Data warehouse platform to support heterogeneous databases.

DW / BI Implementation ;Gathering requirements from users (CNA, US)'Writing , Analyzing , reviewing Target-to-Source (T2S) document, finding architectural defects Gathering requirements from the onsite coordinator on a daily basis( in initial two projects) and developing Mappings/Session/Workflows ,Unit Test Cases and Code review Checklist.Developing PL/SQL stored procedures for needed business logic and calculations ;Successfully delivered 3 big data warehousing projects ;Acknowledged and recognised as the data warehousing /BI expert in the firm and highly appreciated by senior management for guiding the design and ETL development.