Big Data Governance

Deepika (DEE) S. Pandian, PMP

TS/SCI with CI Poly Clearance

Leesburg, VA 571-***-**** *********@*****.*** [LinkedIn Profile] [Neo4J Interview]

Professional Summary

Experienced Federal Data Leader and Technical Architect with over 20 years of expertise in delivering innovative, scalable, and compliant data solutions for federal projects. Proficient in Big Data technologies, data governance, ML/AI, and systems architecture, with a proven track record of leading cross-functional teams and driving multimillion-dollar initiatives to success. Adept at aligning technical strategies with federal compliance standards such as NIST, FEDRAMP, and CMMC.

Key Skills

Federal Compliance: NIST, FEDRAMP, RMF, CMMC

Leadership & Project Management: Agile, Scrum Master, PMP Certified

Big Data & Cloud Technologies: Neo4J, ELK Stack, Hadoop, AWS Glue, Redshift, GCP BigQuery

Data Governance & Cataloging: Policies, frameworks, and data quality initiatives

Machine Learning & AI: TensorFlow, NLP, Anomaly Detection, MLOps with AWS SageMaker, MLFlow

Programming & Analytics: Python, C#, Java, SQL, R, Tableau, Dataiku

Team Development: Mentorship, motivation, and cross-department collaboration

Professional Experience

Chief Data Officer IBM (10/2023 – Present)

Lead four teams of 12–16 engineers to enable data transformation and governance for federal datasets.

Developed ETL pipelines using AWS Glue and Cloudera Flow Manager, mapping datasets like UNICORN and MIDB.

Established robust data governance frameworks, ensuring data quality, integrity, and compliance.

Delivered MLOps pipelines integrating AWS SageMaker with GitLab and S3 for model deployment.

Authored key compliance documents, including STP/SSP reports, achieving ATO/IATT certifications for high-side systems.

Conducted trade studies and implemented data cataloging solutions to enhance federal data usability.

Principal Big Data Technical Architect Global InfoTek, Inc. (9/2020 – 7/2022)

Designed scalable Big Data architectures using Neo4J, ELK Stack, and AWS for federal applications.

Led ML projects to identify anomaly logs, employing NLP and classification algorithms.

Built data integration workflows from Oracle to AWS OpenSearch using AWS Glue.

Modeled and transformed data for graph analysis in Neo4J, creating actionable insights for federal stakeholders.

Customized Kibana dashboards and implemented alerting systems to monitor critical metrics.

Cybersecurity & Big Data Solutions Architect Jacobs Technology (03/2012 – 9/2020)

Directed a team of 19 professionals across multiple departments, delivering federal cybersecurity and Big Data projects.

Spearheaded three multimillion-dollar federal programs, driving secure data management and compliance.

Developed scalable systems using Cloudera Hadoop, RabbitMQ, and Elastic Stack, optimizing multi-terabyte datasets.

Established vulnerability management workflows, ensuring alignment with RMF standards.

Enhanced decision-making through ML/AI solutions, including NLP and anomaly detection.

Lead Software Engineer LSQ Funding Group (05/2008 – 03/2012)

Modernized legacy systems, reducing operational costs by 60%.

Designed scalable applications for data analysis, extraction, and retrieval.

Directed software development initiatives using C#, Java, and SQL Server.

Senior Software Engineer Mitsubishi Heavy Industries, Japan (05/2006 – 05/2008)

Developed cross-border ticketing solutions, improving workflow efficiency for multinational teams.

Consulted on system solutions to address evolving client requirements in Japan and India.

Software Engineer LSQ Funding, USA (07/2001 – 05/2004)

Software Developer SGJ Inc, India (07/1998 – 11/2000)

Education

Master of Science, Computer Information Systems

University of Phoenix, Tempe, AZ (03/2004)

Postgraduate, Computer Science

Manonmaniam Sundaranar University, Tamil Nadu, India (01/2000)

Certifications

Project Management Professional (PMP)

CompTIA Security+

Neo4J Certified Professional Developer

Dataiku ML/Core Designer

GCP BigQuery for Data Warehousing

IBM Blockchain Essentials

Key Federal Projects & Accomplishments

Created a five-node ELK cluster to analyze COVID Netflow data with Kibana and Elastic Search.

Implemented Neo4J-based graph analytics for classified federal data.

Delivered STP/SSP reports to secure ATO/IATT certifications, ensuring system compliance.

Designed anomaly detection models for federal cybersecurity, leveraging MLOps pipelines to streamline ML and AI integration

Personal Projects

Built a COVID data analysis platform integrating ELK Stack, AWS QuickSight, and Neo4J for global trend insights.

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