SUMMARY

• Over 9+ years’ experience in designing, planning, maintaining and implementing system applications both on premise and in cloud.
• Highly skilled team - oriented AWS Cloud Solutions Architect, Big Data Architect, and a Certified Data Scientist.
• Experience working as a cloud solution architect for clients, managing server infrastructures, migration and data center operations. Implementing upgradable, scalable, hyper-converged infrastructure and micro-services across multiple platform (Linux, Windows, AWS).
• Expert in product support and analytics insights (Business Intelligence) with strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models by creating algorithms.

TECHNICAL SKILLS

SKILLS: Orchestration Services ECS, Docker Containers, Cloud Formation, Elastic Beanstalk, Cloud Computing - Amazon Web Services (EC2, EBS, S3, AWS, Azure, BCP & DRP, PKI, IAM, AMI, VPC, VPC Peering, NACL, Security Groups, Route53, Auto Scaling, ELB, SNS, Cloud Watch, Terraform, Ansible, AWS Inspector, AWS Shield, Guard Duty, CloudFormation, Kinesis, CI/CD, Jenkins, GitHub, KAFKA,EMR,TALEND

DATABASE FOCUS: PostgreSQL, MySQL, MicrosoftSQLServer, NOSQL/Dynamo DB, Datawarehouse, Data Validation, Data Analysis, Data Visualization, Data reporting, Data Metric analysis, Data Migration, Business Objects, D3, Map/Reduce, Hadoop, Spark.

Querying Languages: SAS, Python, SQL, R, Scala, and PySpark.

Business Intelligence Tools: Tableau, Power Bi, MicroStrategy, QlikView, Alteryx, Splunk

PROFESSIONAL EXPERIENCE

Confidential, Washington DC

Senior Big Data Architect

Responsibilities:

• Developed cost/benefit modeling and created compelling business use cases/total cost of ownership studies for migration.
• Configured/Customized the AI/BI Applications as per the client’s requirement.
• Maintained and configured user accounts for dev, QA, and production servers.
• Built an end-to-end real-time data pipeline by building four micro-services on top of Apache Kafka for data processing.
• Developed enterprise platforms using Big Data tools and technologies -( Hadoop, Spark, Hive, Impala, Zeppelin, Jupiter
• Responsible for ingesting large volumes of IOT data to Kafka.
• Developed Microservices with Java using Spring Boot IDE.
• Worked on identifying present Scripted syntax Jenkins pipeline style and suggested to changing to Declarative style for reducing deployment time.
• Provided expertise and hands on experience working on Kafka connect using schema registry in a very high volume environment (~900 Million messages).
• Provided expertise in Kafka brokers, zookeepers, KSQL, KStream and Kafka Control center.
• Provided expertise and hands on experience working on Avro Converters, JsonConverters, and StringConverters.
• Provided expertise and hands on experience working on Kafka connectors such as MQ connectors, Elastic Search connectors, JDBC connectors, File stream connector, JMS source connectors, Tasks, Workers, converters, Transforms.
• Provided expertise and hands on experience on custom connectors using the Kafka core concepts and API.
• I Had A Working knowledge on Kafka Rest proxy.
• Ensured optimum performance, high availability and stability of solutions.
• Created topics, setup redundancy cluster, deploy monitoring tools, alerts and has good knowledge of best practices.
• Created stubs for producers, consumers and consumer groups for helping onboard applications from different languages/platforms. Leverage Hadoop ecosystem knowledge to design, and develop capabilities to deliver our solutions using Spark, Scala, Python, Hive, Kafka and other things in the Hadoop ecosystem.
• Wrote Kafka producers to stream the data from external rest APIs to Kafka topics.
• Used and implemented several Security groups in AWS cloud and working with S3.
• Good experience with continuous Integration of application using Jenkins.
• Used chef, Terraform as Infrastructure as code (IaaS) for defining Jenkins plugins.
• Responsible for maintaining inbound rules of a security group(s) and preventing duplication of EC2 instances.
• Spun up servers such as Jenkins and automated builds. for development.
• Built intuitive and interactive Dashboards as per client requirement for their internal cooperate affairs.
• Provided in-depth Onsite and remote technical guidance to customers to ensure project implementation
• Worked collaboratively in a cross functional team which includes (Product Management, Partner Operations, Development).
• Gathered, Analyzed and documented pre-project and post project requirements.
• Partnered with the sales team to design solutions for customers that drive AWS adoption and revenue
• Engaged with C-level executives to define and execute on Enterprise cloud strategies
• Analyzed application portfolios, identifying dependencies & common infrastructure platform components, and assessing migration feasibility
• Built VPCs from scratch, creating private and public subnets, creating security groups and network access lists, configuring internet gateways, OpenVPN, creating AMI, understanding of user access management/role-based access/multi factor authentication and API access, configuration of auto scaling and elastic load balancer for scaling services
• Setup NAT gateway as a route out to the internet for instances in private subnet
• Providing expertise to client's early adoption strategy such as end user training, evangelizing cloud solutions, bringing understanding, experience and best-practice in the AWS cloud ecosystem
• Partner with the sales team to design solutions for the customer to drive AWS adoption and revenue
• Configuring and deploying micro-services and instances, EC2, ECS, Auto-scaling, S3, Security groups using Cloud-formation
• Deployed DevOps techniques and practices like Continuous Integration, Continuous Deployment, Test Automation, Build Automation and Test-Driven Development to enable the rapid delivery of working code
• Used Terraform in building infrastructure to host web/applications and RDS infrastructure; using AWS cloud provider.
• Acted as a liaison between Customers and Product Management to drive product development.
• Collaborated with the sales team on existing customers up-sell and cross-sell opportunities.
• Manage multiple concurrent deployment projects.
• Applied knowledge of technologies and protocols to support identity federation and robust access control models, such as SAML 2.0, WS-Federation, OAuth, and OpenID Connect.
• Applied software development experience to build Multi-Tier applications when working with customers.
• Utilized knowledge of typical enterprise identity life cycle management processes and standards.
• Provided mentoring, guidance, and expertise to less experienced team members.

Confidential, Washington DC

Enterprise Solution Architect/Sr DevOps Engineer

Responsibilities:

• Engaged customers - collaborated with ad tech sales managers and sales executives to develop strong customer relationships, vetted requirements upfront, and drive excitement for the right ad tech solution that achieves the customer’s business outcomes.
• Managed and delivered ad tech integration engagements in services such as EC2, S3, RDS and other AWS services.
• Responsible for launching Amazon EC2 cloud instances using amazon Web services (Linux) and configuring launched instances with respect to specific applications and regions.
• Responsible for S3 buckets creation, policies and the IAM role based policies.
• Build Servers using AWS, importing volumes, launching EC2, RDS, SQS, SNS, Lambda, and Kinesis and creating VPC from scratch based on client specification.
• Worked as Subject Matter Expert in AWS Public cloud for the company and designed architect and operating solutions built on AWS.
• Provide technical guidance concerning business implications of application development projects.
• Leveraged ETL programming skills in open source languages including Python, Scala, and SQL on various frameworks using Apache Spark.
• Used the services of AWS Cloud technologies at IaaS layer (network, compute, storage) and managed services such as RDS, SQS, SNS, Kinesis, Elastic Cache, Elastic Beanstalk, IAM, Cognito and others
• Designed Resiliency, High-Availability, Fault Tolerance, and Scalability in context of AWS Cloud
• Developed Hybrid Cloud environments
• Involved in assessing, planning, designing, and migrating/transforming legacy applications to AWS Cloud
• Worked with cloud native/12-factor application architecture and micro services
• Built and executed micro service applications using Spring Boot, Spring Cloud, NodeJS, python/flask/Django
• Architected stateless and stateful applications for containers and container manager/schedulers such as Kubernetes, AWS EKS, AWS ECS and Docker
• Demonstrated ability to architect and model mission critical solutions leveraging multiple DBMS technologies i.e. Relational, Big Data, NoSQL (K-V stores, document stores, graph and column)
• Experience with event driven and real-time architectures, patterns, messaging and streaming technologies such as using Apache Kafka, AWS Kinesis, Amazon SQS/SNS, Amazon MQ, AWS Managed Services for Kafka etc.
• Used Big Data, analytics and machine learning technologies on AWS such as EMR, Apache Spark, Sage Maker
• Practiced and used software engineering practices using CI/CD and associated toolsets such as git, AWS Code Commit, Jenkins, Travis, Bamboo, Concourse, Salt, AWS Code Deploy, and AWS Code Pipeline.
• Worked with Distributed Systems Architecture, MapReduce and Spark execution frameworks for large scale parallel processing.
• Provided hands-on, expert-level technical assistance to developers.
• Developed and monitored metrics to measure and improve the efficiency of the functional and technical team
• Managed the technical delivery of custom development, integrations, and data migration elements of CRM /Salesforce implementations.
• Developed and maintain working relationships with key vendors so we can maximize our usage of their products.
• Performed extensive Working knowledge of enterprise integration and third-party enterprise integration tools (E.g., Scribe, WebSphere, Informatica, etc.)
• Developed custom solutions and interfaces leveraging the CRM/Salesforce platform
• Worked extensively on Hadoop eco-system components Map Reduce, Pig, Hive, HBase, Flume, Sqoop, Hue, Oozie, Spark and Kafka.
• Worked with all major Hadoop distributions like Cloudera (CDH), Horton works(HDP) and AWS EMR.
• Developed highly scalable Spark applications using Spark Core, Data frames, Spark-SQL and Spark Streaming API's in Scala.
• Gained good experience troubleshooting and fine-tuning Spark Applications.
• Experience in working with D-Streams in Streaming, Accumulators, Broadcast variables, various levels of caching and optimization techniques in Spark.
• Worked on real time data integration using Kafka, Spark streaming and HBase.
• Interacted with NoSQL databases such as HBase and its Integration with Hadoop cluster.
• Performed extracting, wrangling, ingestion, processing, storing, querying and analyzing structured, semi-structured and unstructured data.
• Worked with Hadoop MRV1 and Hadoop MRV2 (or) YARN Architecture.
• Developed, deployed and supported several Map Reduce applications in Java to handle semi and unstructured data.
• Involved in Map side join, Reducer side join, Shuffle & Sort, Distributed Cache, Compression techniques, Multiple Hadoop Input & output formats.
• Experienced in working with csv, text, sequential, Avro, parquet, orc, Jason formats of data.
• Expertise in working with Hive data warehouse tool - creating tables, data distribution by implementing static and dynamic partitioning, bucketing and optimizing the Hive QL queries.
• Involved in ingestion of structured data from SQL Server, My Sql, Tera data to HDFS and Hive using Sqoop.
• Experience in writing AD-hoc Queries in Hive and analyzing data using HiveQL.

Confidential, Washington DC

Senior Data Engineer /Data Scientist

Responsibilities:

• Provided best of breed, fit for purpose data science and architectural recommendations leveraging Cloud &traditional on premise data services.
• Provide detailed, hands-on expertise in creating data, AI, and advanced analytics solutions for clients.
• Responsible for successful delivery of cloud and data science solutions and services in a client consulting environment.
• Developed and implemented platform architecture as per established standards.
• Formulated architectural plans for mitigation purpose.
• Supported integration of reference architectures and standards.
• Utilized Big Data technologies for producing technical designs.
• Prepared architectures and blue prints for Big Data implementation.
• Evaluated and documented use cases and proof of concepts.
• Participated in learning of tools in Big Data systems.
• Installed and maintained Big Data systems on laptops with Linux.
• Designed data architecture, AI, and advanced analytics proposal support, design and delivery.
• Defined key business problems to be solved, formulate mathematical approaches and gather data to solve those problems, develop, analyse/draw conclusions, test solutions and present to client.
• Assisted in assuring client satisfaction and maintaining a strong client relationship through delivery excellence.
• Used predictive modelling, optimization, and/or machine learning analytics techniques and tools/programming languages.
• Worked independently, leading a work stream effectively on a team.
• Used statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Performed machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Used advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Performed statistical and executed several data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Involved in querying databases and using statistical computer languages: R, Python, SLQ for AI and BI reporting.
• Used web services: Redshift, S3, Spark, and Digital Ocean.
• Created and used advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks.
• Analysed data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics, AdWords, Crimson Hexagon.
• Used distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL,
• Created visualizations and presented dashboards for stakeholders using: Periscope, Business Objects, D3, gplot,

Confidential, PA

Data Analyst/Tableau Developer

Responsibilities:

• Identified and documented limitations in data quality that jeopardized the ability of internal and external data analysts.
• Created complex SQL queries and scripts to extract and aggregate data to validate the accuracy of the data. Performed daily integration and ETL tasks by extracting, transforming and loading data to and from different RDBMS. Utilized SSIS for ETL data modelling, data migration, and analysis. Business requirement gathering and translating them into clear and concise specifications and queries.
• Prepared high level analysis reports with Excel and Tableau, providing feedback on the quality of data including identification of billing patterns and outliers. Analysed and Assessed invalid and missing data in the All Payer Claims Data.
• Used SAS to mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis, documenting the extent to which data fails to meet threshold reporting requirements. Created T/SQL statements (select, insert, update, delete) and stored procedures.
• Developed and lead a seven-man project team to implement data visualization tools providing an easy to understand interface for end users to quickly identify key themes within their Data. Designed Reports per client specifications and using Excel file, SQL Server and Oracle databases.
• Created Tableau scorecards, dashboards using stack bars, bar graphs, scatter plots, geographical maps, heat maps, bullet charts, Gantt charts thereby demonstrating key information for decision making. Utilized SAS, and other software, to provide “ad hoc” reporting, tables and listings, and graphs for clinical trials data, regulatory submissions, Risk Based Monitoring, and publications.
• Developed and produced peer quality metrics performance validated data and processes to ensure accuracy, completeness, and consistency of data using SAS. Created complex reports including Detail Level Transaction report, monthly Aging, YTD cash goal Reports, and Quarterly reports by creating multiple queries.
• Hands on experience extracting, manipulating and building complex formulas in Tableau for various business calculations. Key player in resolving reporting and design issues throughout the reporting life cycle.
• Developed SQL queries to extract, manipulate, and/or calculate information to fulfil data and reporting requirements including identifying the tables and columns from which data is extracted. Used SAS to solve problems with data and analytics.