SUMMARY:

• Senior technologist with strong business acumen and technical experience in Big Data and Cloud Infrastructure space. A creative hands on technical leader who excels in designing, building and deploying Big Data infrastructures and analytic capabilities. Equally adept at performing hands on architecture and integration tasks or leading diverse team sets. My expertise lies in enabling business users to leverage customer, financial, and operational information to improve performance, productivity, and profitability. Proven leader in understanding emerging technologies and their role in the big data and cloud eco - systems
• Developed and provided hands on integration of multiple 100 plus node Cloudera and Hortonworks big data environments. Developed automated hands free cluster management utilities that process 50M records daily. Authored engineering trade studies and architected proof of concepts migrating peta-byte scale data frameworks to Microsoft Azure, Amazon Web Services and other Cloud based architectures. Provided cluster usage metrics to senior management identifying key performance indicators of a hadoop cluster infrastructure. Increased the value of data through thoughtful data cleansing/scripting and data validation processes.
• Led the development of big data and analytic workflows for Confidential commercial customer base. Data types delivered to customers included sensor, billing transaction, multi-column and various unstructured data types. Achieved significant business value by creating partnerships among data owners, stakeholders and subject matter experts on consulting engagements. Authored statements of work defining project work, cost and schedule for consultant engagements. Authored multiple procedures and publications bridging technology in the cloud infrastructure and big data analytic skill area.
• Pioneered and delivered a Hadoop based data lake for Merck Manufacturing Intelligence business unit. Cluster was designed on top of Amazon Web Service cloud framework and successfully imported 64 Merck data sets and over 32,000 real time sensor data points. The 500 terabyte platform was built on Apache freeware and Amazon Web Services hardware and storage. Total Cost of platform was less than $300k including labor cost.
• Orchestrated the day to day integration of a large enterprise system across multiple developer, test and infrastructure teams. System consisted of over 1M lines of java code, 220 VM/Linux servers, 12 WebLogic domains and multiple Oracle 11 databases. I was personally responsible for ensuring system health to meet critical development and operations transition timelines. Lockheed Martin achieved significant award fee with transition of this key national intelligence program.
• Served as a key technical contributor to the Confidential Requirements Management System (RMS). The RMS system provides end to end management of national and strategic imagery collection, exploitation and dissemination of critical geospatial data. Provided consolidated management of over 150 world-wide servers with over 5,000 users.

TECHNICAL SKILLS:

Cloud Architecture: Microsoft Azure, Amazon Web Services, IC-GovCloud

Microsoft Azure: VM s, HDInsight, Machine Learning, Stream Analytics, Data Factory, Event Hubs

Amazon Web Services: EC2, S3 Storage, Redshift, Elastic Map Reduce, Kinesis Streams

Data Analytics: Data manipulation, cleansing and analysis on large data sets, Tableau, Pentaho

Hadoop EcoSystem: HDFS, Sqoop, Flume, Kafka, NiFi, Spark, Accumulo, Hbase, Hive, Cassandra, Pig

Database Engineering: Designed and served as Database Administrator for a large Oracle system; other experience includes MySQL, NoSQL, and Hadoop databases

Linux: Stack Level Tracing, Performance Monitoring, Software Package Engineering, Puppet

Version Control: Subversion, Rational Clearcase, Git

Programming: UNIX shell scripting, Python

PROFESSIONAL EXPERIENCE:

Confidential, Chevy Chase, Md

Principle Engineer

Responsibilities:

• Lead the day to day operational ingestion and processing of over 50 Department of Homeland Security data sets on Cloudera and Hortonworks Platforms. Data flows utilize Flume/NiFi-> Hive/Accumulo->SolR Indexing with a java based analytic GUI tool set.
• Oversaw the cost and engineering efforts to assess transitioning data framework from in house data center to Microsoft Azure platform using HD Insights, Data Warehouse, Stream Analytics and Data Factory consumption model.
• Formulated the engineering plan to move current infrastructure to Amazon Web Services framework to leveraging EC2, S3 Storage and Amazon Redshift capabilities.
• Created several automated scripts to ingest data, assess cluster state of health and provide key database metrics for management use. Led engineering development efforts to further use of puppet baseline management.
• Provide engineering guidance for business intelligence teams using Tableau and Qlikview analytic tools.
• Developed data cleansing scripts to improve analytic capabilities. Consolidated and validated data from a vast range of sources from applications and databases to files and Web services. Ensured data quality and data governance in accordance with Homeland Security directives.

Confidential, Philadelphia, Pa

Consultant

Responsibilities:

• Delivered MapR/Hortonworks/Cloudera architecture designs to Confidential.
• Integrated Spark into MapR eco-system on Confidential proprietary data platform.
• Assisted clients in reshaping business processes to analyze data using Amazon Web Service, Microsoft Azure and Apache Hadoop Eco-system components
• Provided engineering blueprints that transition data from data warehouse into Hive and HBase data stores.
• Provided database architecture designs to design hadoop based data lake stores.
• Created data flows utilizing Sqoop, Flume, Spark, Hive, HBase components creating business value from disparate data points.
• Designed analytic data models sourced from multiple and varied data sets.
• Delivered process driven business intelligence platforms aligning data with appropriate toolset and analytic framework.

Confidential, Philadelphia, Pa

Consultant

Responsibilities:

• Developed cloud based strategies that improve the value of analytical data and streamline the flow of data through an organizations enterprise using MapR, Cloudera, Hortonworks and Apache Hadoop software framework. Architected a a cloud based replacement for legacy systems that utilized Linux clusters to make data available 24/7.
• Redeployed hosted application on Amazon Web Services using Elastic Load Balancing, Amazon Elastic Compute Cloud (EC2), Amazon Route 53 for DNS, Amazon Relational Database Service (RDS) and CloudFront for content delivery.
• Set up a Hadoop based data ingestion engine using Apache freeware on Amazon Web Services cloud. The stack built on Red Hat Linux included Hadoop/HDFS, Sqoop, Hive, and HBase. Ingestion engine is capable of ingesting from multiple data sources such as Oracle and Informatica.

Confidential, West Point, Pa

Consultant

Responsibilities:

• Lead the technology evaluation, recommendation and implementation for creating a flexible big data lake using the hadoop ecosystem.
• Authored the architecture development, data integration planning and program execution to transition Merck Vaccines Manufacturing Intelligence & Integration System to a Apache hadoop big data architecture.
• Authored the installation, configuration and checkout design documentation for Hadoop/hdfs, Hive, HBase, NoSQL, and Cassandra software packages.
• Architected and executed the detailed data ingestion patterns using Sqoop, Flume and raw file ingestion to create the hadoop data lakes.
• Wrote detailed installation scripts to for Hadoop, Hive, HBase, Sqoop, Flume, Cassandra
• Conducted proof of concept experiments to on Hadoop stack to verify data quality and integrity.
• Provided linux and hadoop performance monitoring support for Hadoop infrastructure.

Confidential, Laurel, Md

Systems Engineer Senior Staff

Responsibilities:

• Responsible for the creation of a big data strategy and engineering roadmap to define and implement the Big Data Architecture for the Army Intelligence and Security Command Red Disk program.
• Architected big data cloud infrastructure that ingested, processed and stored raw intelligence data from over 30 data sources exploiting multiple intelligence data feeds.
• Created DODAF SV-1, SV-4 and SV-6 Views for the cloud based INSCOM Red Disk architecture
• Architected and configured Hortonworks and Cloudera big data frameworks
• Provided engineering leadership in all phases of hdfs performance tuning. This effort included hdfs NameNode, DataNode, Job/Task Tracker, Core Services and Bulk Data Transfer performance.

Confidential, Valley Forge, Pa

Systems Engineer Senior Staff

Responsibilities:

• Managed and orchestrated the day to day integration of a large cloud based business intelligence across multiple developer, test and infrastructure teams. Ensured environment stability and uptime to support test and integration activities.
• Led the weblogic integration and daily code deployments providing near 100% uptime for test and development efforts.
• Architected the Red Hat linux operating baseline used on over 200 operational servers.
• Lead the performance monitoring and troubleshooting of o/s using various tools and utilities. Performed stack trace analysis of problem applications.
• Assisted Database Admin team with a rollout plan of the Oracle DB servers. Led key performance troubleshooting and monitoring of Oracle Database servers using OEM tools. Performed benchmark testing of key SQL queries.
• Led the integration of SAP Business Objects into the programs baseline. Configured and set up Universes and performed key benchmark performance testing.