PROFESSIONAL SUMMARY:

• Managed Services - Big Data Platform, Analytics, Data Pipeline Engineering, Machine Learning-Data Science, Data Visualization, Application Development, DevOps, GCP, AWS, Azure & IoT.
• Building data pipelines for big data and cloud-based applications using Scala & Python (Glue, Dataflow, Spark, Dataproc, Pub Sub, Kafka, Kinesis, Ansible, Docker, EMR, Big Table, Dynamo, Cassandra, Hbase, Spanner, Cloud SQL, Cloud functions, Lambda, Kubernetes & Airflow).
• Securing big data platforms on-prem, hybrid and in the cloud using a combination of network isolation, encryption of data at rest and in motion in combination with information and application security and assurance best practices.
• Building and configuring machine learning algorithms on Cloud ML, TensorFlow, Keras, AzureML.
• Kafka-Confluent & Spark SME on AWS & GCP platform. Configuring Confluent schema registry, KSQL server, Kafka connect workers, Kafka brokers & producers, zookeeper nodes, confluent control, Kafka streams app and microservice. Proficient with Confluent Control Center (monitoring cluster, setting alerts and triggers, ensuring end to end delivery of all messages in queue, optimize and performance tuning of Kafka cluster.
• Managed L1, L2, L3 production support for big data platform, data visualization & cloud applications (Kafka-Confluent, Spark, Hadoop-HDFS, Hive-Hue, Impala, BigQuery, Snowflake, Redshift, S3, Cloud Compute, Cloud Storage, Nexus, Trifacta, Alation).
• Active and proactive monitoring of production nodes using tools like Stack driver, Cloud Watch, Zabbix, Nagios, Grafana, log stash, Kibana, elastic search & cloud watch for platform support.
• Monitoring, installation, configuration, administration, troubleshooting and maintenance of Kafka, Spark & Hadoop Distributed Systems on multi-node clusters on 24/7 production systems.
• Proficient in YAML, REPL, VIM, YUM, PIP, RPM, shell scripting and all platform system commands in Linux/Unix platforms.
• Implementing automation, migration, security enhancements and process improvements.
• Datalab, Dataprep, Data Studio, Data Science Studio (DSS - Dataiku), Spotfire & Tableau SME.
• Creating SOP’s for support and incident resolution tasks.
• Access management, Security - Kerberos, resolving incidents, tasks, projects within SLA.
• Troubleshooting and coordinating with vendors for hot fixes and complex implementations.
• Extensive use of Linux clients (mobaxterm, putty), editors (vim & WinSCP to run configuration commands, disk clean up, memory monitoring, all support and DevOps tasks.
• Proficient with collaborative tools like box, slack, yammer, jive, service now, JIRA & confluence to perform big data platform, cloud & analytical tools applications support task.
• Consolidating structured and unstructured data from disparate data sources to build data lakes and data products and eventually deploy or integrate solution with other applications in hybrid cloud and on-prem production systems.
• Build data products by extracting data from IoT devices and do complex event processing for decision engines, predictive models and live streaming dashboards for monitoring.
• Rapid prototyping of products & solutions after analyzing business problems and going through iterations and simulations of possible solutions; thinking outside the box and challenging status quo techniques for problem solving.
• Critical thinking & domain knowledge in several industries including: Banking, Finance, Telecommunications, Oil & Gas, Pharmaceuticals, Healthcare, Supply chain & logistics, Marketing, Consulting, Professional Services and Information Technology.

PROFESSIONAL EXPERIENCE:

Confidential - Dallas, TX

DevOps / Big Data SME / Data Engineer / Business Intelligence Consultant-SME

Responsibilities:

• Design & implement, support and maintain end-to-end big data platform, data lakes, analytics and cloud solutions in Google Cloud Platform, Amazon Web Services, Azure, Snowflake Computing and On-prem big data platforms in Cloudera, Horton works and mapR. Snowflake, Big Query & Redshift POCs for evaluating modern data warehouses. Snowflake SME.

Confidential - San Jose, CA

Big Data Consultant / SME

Responsibilities:

• Implementing and supporting big data and data pipeline engineering solutions using CI/CD, GCP, AWS, Kafka-Confluent, Spark & HDFS data lake ecosystem. Ingesting data from HDFS, S3, Cloud Storage, Kinesis, Pub Sub processing and moving to operational data stores (BigQuery, Big Table, Redshift, Dynamo, S3, EMR, Dataproc etc. into JSON, Parquet, Avro, Protobuff formats. Extensive use of Dataflow/PySpark for creating ETL jobs. Executing SQL & HiveQL queries using PySpark. Performing aggregations and transformations using data frames (RDD operations). Configuring spark execution engines on consumption tools like Dataiku, Spotfire & Tableau. Implementing Spark context apps in Scala using databricks-spark custom libraries. PySpark/Dataflow pipelines.

Confidential - Dallas, TX

Big Data Consultant /SME

Responsibilities:

• Implementing data pipelines for IoT applications - Connected Room, Digital Check-In, Digital Check-Out and Explore. Developed and maintained data lake in S3 and used Glue, EMR, Spark and Kafka/Kinesis for data processing data between cloud native IoT apps and redshift & snowflake Datawarehouse. Provided data to data scientist for machine learning models and data products for these products.

Confidential - New York City, NY

Big Data Consultant / SME

Responsibilities:

• Implementing end to end data pipelines for streaming analytics. Running operations on paired RDDs. Integrate Spark streaming with Apache Kafka for fast data analytics and real time machine learning. Monitoring scheduled jobs and troubleshooting any errors in production. Documenting run books, standard operating procedures & governance on data lake. Integrating deployments with CI/CD - docker. Setting up templates (Spark clusters) for easy deployments - cloud formation. Tuning and configuring drivers and executors on spark. Utilized AWS stack for big data for entire deployment (S3, DMS, Dynamo, Redshift, Lambda, Glue, EMR, Kinesis, RDS, Athena, EMRFS). Migrated to open source big data stack on AWS platform (Spark, Kafka, Presto).

Confidential - San Francisco, CA

Big Data Engineer Lead

Responsibilities:

• Implemented contract and provider predictive analytics data product. This data product included a series of data products tracking contract and provider metrics, KPI’s, regression analysis with contract coverage, clinical studies, SLA’s, drug manifestations, etc.

Confidential - New York City, NY

Big Data Engineer Lead

Responsibilities:

• Designed and developed operational business insights and data products for real world research data on hybrid cloud platform.
• End to end implementation of product; data modeling, data mining, ETL, ELT, database environment deployment and administration, data wrangling, data product consolidation and release with modeling algorithms for predictive and prescriptive analytics.
• Compliance and governance with HIPAA and other healthcare industry codes like ICD-9, 10, CPT, etc.

Confidential - St. Louis, MO

Big Data & Analytics Consultant / SME

Responsibilities:

• Redesigned and developed a global supply chain dashboard and guided analytics operational intelligence tool using AWS data pipeline for ETL and consuming in Spotfire.
• Designed a reporting new data model from data-warehouse (Teradata), other big data sources (structured & unstructured) and data virtualization layer (Info model-Spotfire) to feed the Spotfire analytic data products and dashboards with optimum performance.
• Refactoring and development of reports and dashboards using Spotfire and extending the platform for extra and custom capabilities with iron-python, JavaScript and R.
• Setting up and configuring automation services for data refreshes and migrations to different Spotfire server environment and deploying models to production.
• of developers and analysts, knowledge base documentation, setting up a Spotfire BI standards center of excellence with best practices use cases well documented.
• Collaborated with data science team to integrate machine learning algorithms and predictive analytics data products within the Spotfire platform.
• Planned out and executed Spotfire patch and upgrade for 7.0 & 7.5

Confidential - Houston, TX

Business Intelligence Architect

Responsibilities:

• Designed and developed operations real-time analytic data products and dashboards for production engineering support, finance, water disposal, production optimization and consolidated data products using Teradata, Spotfire for business units. Built and supported ETL data pipeline.

Confidential - Washington, D.C

Business Intelligence Consultant

Responsibilities:

• Designed and developed predictive analytics data product using tableau for managing business loans to small business, farmers, etc. Product included weather data, census data, loan status data, etc.

Confidential - Plano, TX

Big Data Analytics; Solutions Architect

Responsibilities:

• Integrating SAS & R into Spotfire & Tableau to build dashboards and analytic products for different lines of business.
• Developed automated workflows and data products end to end for Governance and compliance department.
• Worked with offshore administration teams maintaining Spotfire and tableau server environments. Pioneered member of team that established ETL and BI center of excellence.
• Transitioned to data science team building machine-learning algorithms, text mining and other data products to support different LOB’s and enable bank to meet SLA’s with client agreements.

Confidential - Dallas, TX

Java Developer / SQL Developer / Business Systems Analyst

Responsibilities:

• SQL scripting & tuning, stored procedures, reporting, systems design, analysis & implementation, enterprise data management, requirements gathering, technical & operational support using Microsoft technology stack, SAP & Oracle ERP. Application design and development.
• Designed, developed & implemented ERP system. Requirements gathering & business process modeling for enhancements to ERP system. Logical database design for applications & maintenance of Ops prod DB.