Data Analyst Governance

PROFESSIONAL SUMMARY

Data Analyst with *+ years of experience specializing in structured data management, validation workflows, and process automation. Core expertise includes Python and SQL for data manipulation, with advanced proficiency in Excel, Google Sheets, and custom scripting. Skilled in designing and maintaining data ingestion pipelines, anomaly detection routines, and data transformation processes across relational databases such as PostgreSQL and Snowflake. Adept at integrating multi-source data and upholding strict confidentiality and data governance standards. Known for delivering clean, reliable datasets and supporting effective decision-making in dynamic, security-focused environments.

WORK EXPERIENCE

Ndustrial, Data Analyst Jan 2024 - Present

●Developed and maintained data ingestion pipelines using Python and SQL to consolidate telemetry from IoT devices, utilities, and SCADA systems, supporting reliable and timely facility analytics.

●Created structured data models in Snowflake and Google Cloud Platform, allowing for efficient data storage and retrieval to meet the demands of large-scale industrial energy datasets.

●Built workflows that validated, tagged, and organized incoming facility data, ensuring datasets remained accurate, up-to-date, and ready for downstream analytics and reporting.

●Improved data quality by implementing anomaly detection routines, flagging inconsistencies or sensor malfunctions that could impact the accuracy of operational dashboards.

●Documented data transformation processes and maintained clear version control on data models, supporting transparency and traceability throughout the analytics lifecycle.

●Integrated data from multiple sources and standardized naming conventions, making it easier for analytics teams to identify trends in energy usage and production efficiency.

●Supported the development of real-time dashboards using tools such as Google Sheets and custom SQL queries, helping operations teams quickly identify opportunities for energy savings.

●Worked closely with analytics and product teams to review requirements, clarify data needs, and ensure that data pipelines delivered actionable insights for workflow automation.

●Participated in internal reviews to identify data gaps, suggested improvements to data collection strategies, and contributed to scenario documentation for operational decision-making.

●Helped define best practices for data governance and security, maintaining confidentiality and integrity of sensitive industrial facility data in compliance with organizational protocols.

Ryft, Data Engineer Jun 2021 - May 2023

●Built and maintained structured datasets in PostgreSQL and Google Sheets to define key financial market entities and support real-time risk analytics for payment compliance workflows.

●Tagged, validated, and organized high-volume transaction data from banking and regulatory sources, ensuring accuracy and consistency for downstream fraud detection systems and compliance audits.

●Created and updated internal documentation, including data dictionaries and naming conventions, to support version control and ensure clarity across evolving financial data models.

●Integrated multi-source financial and regulatory inputs into a unified dataset, providing reliable data foundations for scenario simulations and compliance assessments.

●Analyzed data pipelines to identify gaps or inconsistencies in payment records, flagging anomalies to protect the integrity of risk models and enhance anti-money laundering controls.

●Contributed to team briefings by preparing data-driven summaries and scenario reports, supporting decision-making for new product launches and risk strategy sessions.

●Utilized advanced Excel functions and Google Sheets scripts to automate data validation, streamline reconciliation of cross-border payment flows, and reduce manual reporting errors.

●Supported research coordination by compiling open-source intelligence (OSINT) and academic reports relevant to payment fraud trends, integrating findings into structured data repositories.

●Worked directly with the Data Manager to implement strict data security protocols and confidentiality practices, ensuring sensitive payment and customer data remained protected at all stages.

●Participated in internal review sessions to propose improvements for data ingestion processes, helping adapt risk analytics pipelines to evolving compliance requirements and market dynamics.

TECHNICAL SKILLS

Databases: PostgreSQL, Snowflake, Relational Databases

Cloud Platforms: Google Cloud Platform

Programming Languages: Python, SQL

Spreadsheets & Scripting: Excel, Google Sheets, Google Sheets Scripts

Security & Research Tools: OSINT Tools, SCADA Systems, Version Control, Data Governance Technologies, Confidentiality Protocols

Data Engineering & Processing: Data Ingestion Pipelines, Data Validation Workflows, Anomaly Detection Routines, Data Transformation Processes, Data Tagging Tools

EDUCATION

Master of Science in Computer Science, Computer Science Aug 2023 – Dec 2024

University of Illinois Springfield

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