SUMMARY:

• Seventeen years spread between:
• 12 years Aerospace and 5 years private sector

KEY STRENGTHS INCLUDE:

• Big Data Engineering; Hadoop
• Data Analysis; Statistics, Physics
• Script writing (Bash, Perl, Python, SQL)
• Pipeline Development; Linux OS
• Teaching/Training others
• I fully automate the delivery of timely, accurate, meaningful data.

TECHNICAL SKILLS:

• Bash, Perl, Python, MySQL
• Linux OS, Ubuntu
• Hadoop and AWS EMR
• Hive, Spark, Redshift
• R, R Studio, knitr
• QlikView, Tableau html, PHP, JSON
• VMware, Virtual Box
• Video Games / gaming, MMO development
• GIT, P4V, Chef
• C/C++, GDB, Visual Studio, FORTRAN, Java
• Splunk, OpenStack, Kibana
• Load balancing clusters, VIP, DNS
• Data Warehouse, NFS, Filers, ETL, Metadata, Grids
• Ethereal, Wireshark, TCP dump
• Windows OS, Unix OS including Redhat Linux, RHEL, FreeBSD, Fedora, CentOS, Ubuntu
• Weight Lifting, Mountain Biking, Basketball
• Fantasy Football
• High Frequency Trading Algorithms

WORK EXPERIENCE:

Confidential, Irvine, Ca

Data Engineer / Data Analyst / Hadoop Development

Responsibilities:

• Built an in - house Cloudera Distributed Hadoop Confidential multi-node cluster.
• Eight weeks to fully deploy and configure. This includes hardware and network specifications, meta-data creation which brings structure to the data, pipeline development used to move and load data on to the cluster, version control of any scripts used in this pipeline, re-processing procedures and scripts used in the case of data loss and recovery, log rotations used to prevent exceeding disk space at every point along the pipeline.
• This pipeline is highly-available and durable. This means, to the user, the data is always available and never lost. I can talk more about putting tests in place to ensure data integrity; Accuracy, Completeness, Update status, Relevance, Consistency across data sources, Reliability, Appropriate presentation and Accessibility.
• Built a multi-node AWS, Spark, YARN, EMR, S3 cluster. Six weeks to build a fully automated pipeline. EMR is an Elastic Map Reduce Pipeline. You only deploy the cluster when you need it which reduces cost. Amazon clusters can immediately expand to two hundred nodes. Larger than that is possible with special request. This is a real option for almost any sized company.
• Used HiveQL to create data base structure. Pending data complexity, this can quickly reach thousands of lines in an HQL script. In this case I would build a tool for auto-generating the HiveQL needed for the data structure.
• Utilized bash and Python to automate scheduling of jobs. Created job dependencies.
• Created and scheduled ETL jobs from hand built code.
• Wrote all queries needed to JOIN and aggregate data. I wrote hundreds of queries for both the BI team and Telemetry teams over my two years with Obsidian.
• Used both aggregate and analytic functions in SQL.
• Used MySQL, Hive and Spark for query writing.
• Built a Web Server with PHP MySQL connector for presenting charts.
• Used R and R Studio for statistical models and creating executive reports.
• Used statistical inference, linear regression and maximization techniques.
• Created testing environments on virtual hosts.
• Fully tested Hewlett Packard's big data solution; Vertica.
• Comfortable working with Python’s NumPy, scikit-learn, pandas and Jupyter notebook. Comfortable with Multiple regression, Logistic regression, KNN, SVM, Random Forests, Ensemble models and others. Causation versus correlation, R squared, heteroscedasticity, MAE, MSE, RMSE, Random Search Cross-Validation and their uses.
• Trained on Tableau. Comfortable using Tableau.

Confidential, Burbank, Ca

Data Service Reliability Engineer

Responsibilities:

• Big Data Engineer; Built solutions needed to maintain the health of Big Data pipelines. Worked with Big Data Architects on improvements needed for future pipelines.
• Built a fully automated a disk cleanup solution for over 3000 serving nodes. Selected finalist in company-wide tech solution competition.
• Service Reliability Engineer maintained sight-up on a production system.
• Debugged mission-critical complex search and advertising systems.
• Utilized advanced UNIX knowledge and bash scripting experience.
• Used network knowledge, troubleshooting skills, and coding skills.
• Designed, deployed, monitored, and automated all operational aspects of revenue-critical search and advertising platforms.
• Tool development with Perl and Bash.
• Supported the production system in a 24 x 7 schedule. After hour, weekend and holiday support required.
• Formally trained on GIT, Chef and Hadoop while at Confidential .
• Wrote a tech paper on, “In car navigation with Confidential Maps”. Also known as “dead-reckoning”. This idea could save the planet billions of dollars in costs by eliminating the need of satellites for GPS navigation.

Confidential, Huntington Beach, Ca

Software Engineer

Responsibilities:

• Presented analysis to PHDs and 4 Star Generals.
• Delivered products on time, across multi sites.
• Software integration, development, test, data collection, V&V and analysis for BCTM.
• Upgrading Confidential ’s communications system of systems.

Confidential, Huntington Beach, Ca

Data Analyst / Data Scientist

Responsibilities:

• Created a beam-shape loss model used in production. Used to estimate the signal strength between pulses.
• Created a statistical model used to predict the spin and precession for an incoming re-entry vehicle.
• Contributing significantly to our country’s ballistic missile defense system. Worked with PHDs in Physics and Electrical Engineering.
• Applied physics relating to ballistic motion, radar detection, tracking and discrimination performance for Confidential Aegis Radar systems.
• Four years running Classification Algorithms. This is a machine learning algorithm that uses training data and testing data. Attention to detail needed to produce reliable results.
• Studied Skolnik, Quegan and Kingsley, DiFranco and Ruebin for many years.
• Comfortable with Fourier transforms.

Confidential, Marina Del Rey, Ca

Software Test

Responsibilities:

• Execution of test bed through the use of TCL/TK script writing.
• Software Build Release in large scale build environment; Used Starteam for SDLC (Software Development Life Cycle); similar to Git.