Pamela Austin

Provide business intelligence and analytics consulting for technology company, delivering SQL-based insights and interactive dashboards supporting product and operational decision-making.

• Build Power BI dashboards tracking product KPIs (user engagement, feature adoption, retention) for product management and executive stakeholders.
• Write SQL queries analysing user behaviour patterns, conversion funnels, and feature usage informing product roadmap priorities.
• Partner with product and engineering teams translating business questions into data analysis and actionable recommendations.
• Develop data quality validation frameworks ensuring 99%+ accuracy for executive reporting.
• Create self-service analytics solutions reducing ad-hoc report requests by 60%.

• Designed and implemented automated M&A financial data integration platform using Databricks, Python, and SQL to support due diligence and standalone financial statement preparation for acquisition targets.
• Data Platform Architecture: Built Databricks Lakehouse with medallion architecture (bronze/silver/gold) integrating SAP FICO, Oracle Financials, and legacy ERPs; processed 15.2M+ GL and sub-ledger records with complete audit trail for SOX compliance.
• Financial Consolidation Automation: Developed Python notebooks automating GL extraction, chart of accounts mapping (350+ rules), and GAAP policy harmonization (ASC 606/842); reduced consolidation timeline from 6 weeks to 5 days.
• Accounting Policy Translation: Implemented revenue recognition adjustments, depreciation method harmonization, inter-company eliminations, and purchase accounting logic enabling accurate pro-forma financial statements.
• Demonstrated curiosity and initiative by integrating AI and machine learning capabilities into Databricks-based financial workflows, including automated GL anomaly detection, intelligent chart of accounts mapping, and predictive error flagging, transforming a manual 6-week consolidation process into a 5-day automated pipeline.
• Developed executive presentations and financial models using Advanced Excel (complex formulas, pivot tables, scenario analysis, VBA macros) and PowerPoint to communicate M&A findings, volume trends, and deal impact to C-suite stakeholders, translating complex financial data into clear, actionable narratives for non-technical audiences.
• Led end-to-end deduplication of 150M+ customer and transaction records by designing a business-criteria matching strategy and scalable AWS/Redshift SQL pipeline; orchestrated ETL with AWS Glue and automated CRM syncs to Salesforce using AWS AppFlow and Bulk API 2.0.
• Built production-ready deduplication pipeline in Amazon Redshift using advanced SQL (CTEs, window functions, staging tables) to score, identify, consolidate, and flag duplicates with full audit trail.
• Data Quality & Validation: Built automated trial balance reconciliation framework achieving 99.8% accuracy; identified $12.6M in accounting errors across 4 transactions enabling purchase price adjustments.
• Executive Reporting: Created Power BI dashboards with DAX measures for EBITDA analysis, working capital trends, and financial KPIs; configured DirectQuery to Databricks SQL endpoints with row-level security for deal confidentiality.
• M&A Deal Support: Enabled $450M+ in successful acquisitions; financial forensics uncovered $4.8M revenue recognition error leading to $3.2M price renegotiation on single deal.

Business Intelligence – BI | Predictive Analytics | Process Automation | Data Integration

• Developed predictive ML model to forecast project completion timelines, enabling proactive decision-making, optimized resource allocation, and improved operational efficiency across marketing operations.
• Automated data ingestion pipelines using APIs and Fivetran/dbt, reducing manual data retrieval by 40% and enabling near-real-time analytics.
• Advanced Analytics & Machine Learning: Engineered a predictive machine learning model to forecast project completion timelines, enabling proactive decision-making, optimizing resource allocation, and enhancing operational efficiency across teams.
• Leveraged Advanced Excel (VBA macros, Power Query, dynamic pivot tables, What-If analysis) alongside PowerPoint to develop strategic presentations for Finance, HR, Marketing, and IT leadership; translated complex data from Snowflake and Power BI into compelling visual narratives highlighting volume trends, cost drivers, and actionable recommendations.
• Data Governance & Quality Assurance: Designed and implemented a robust data validation framework, ensuring data integrity and consistency across Snowflake and Power BI reports. Optimized dashboard performance, reducing refresh times by 25% and enhancing real-time data availability for key stakeholders.
• Designed comprehensive data validation framework improving data integrity across Snowflake and Power BI; reduced dashboard refresh times by 25% for real-time stakeholder insights.
• Built interactive Power BI dashboards visualizing compensation trends, workforce costs, and budget allocations for executive-level financial planning and strategic decision-making.
• Integrated Workfront API with Snowflake for centralized marketing analysis, creating unified data models across disparate systems.
• Led Agile ceremonies: backlog management and sprint planning using story points and RICE methodology to prioritize high-impact deliverables.
• Collaborated with Finance, HR, Marketing, and IT stakeholders, leading data discovery sessions and aligning analytics with organizational goals.
• Integrated and optimized data enrichment platforms (ZoomInfo, Salesforce SFDC, Custom Windows Form) enhancing data accuracy and completeness for strategic decision-making.

Product Analytics | Data Integration | CRM Analytics | Campaign Operations | Financial Modelling

• Analyzed campaign performance across multiple marketing channels, measuring ROI, customer acquisition costs, conversion rates, and lifetime value — providing actionable insights that optimized marketing spend and increased campaign efficiency by 22%.
• Maintained data integrity across enterprise platforms by implementing automated quality checks and validation rules using Python and Talend, ensuring 99%+ accuracy for downstream analytics and operational decision-making.
• Analyzed software product performance by tracking user behaviour, engagement metrics, and feature adoption; conducted A/B testing, user research, and competitor analysis to guide product enhancements.
• Designed KPI dashboards in Power BI tracking product success, adoption rates and operational efficiency for executive stakeholders.
• Partnered with cross-functional teams (Product, Marketing, Finance, IT) on process optimization, automation, and analytics-driven decision-making.
• Implemented automated data quality checks using Python and Talend, ensuring high-quality datasets for predictive modelling and reporting.
• Conducted campaign performance analysis measuring ROI, customer acquisition costs, and conversion rates across multiple marketing channels.
• Conducted user research and behavioural analysis to identify high-value customer segments, informing product enhancement strategies and targeted marketing initiatives that increased feature adoption by 23%.
• Initiated budgeting, forecasting, and financial modelling to optimize marketing spending and improve cost efficiency.
• Developed customized Workfront reports to analyze project data, track KPIs, and provide operational improvement insights.
• Utilized Snowflake and SQL to query, clean, and structure large datasets; built ETL pipelines for data transformation.
• Led data governance initiatives ensuring data quality, security, and compliance across platforms.

Finance, Business Intelligence (BI), Healthcare

• Delivered actionable insights for clients across finance, business intelligence, and healthcare through in-depth data analysis and research.
• Finance: Designed data collection methodologies improving accuracy and reliability; analyzed financial data to identify trends, optimize resource allocation, and support investment strategies.
• Business Intelligence: Developed interactive dashboards and reports using Power BI, Tableau, and Excel enabling clients to track KPIs and improve operational efficiency.
• Healthcare: Analyzed large healthcare datasets identifying patterns and quality improvement opportunities; developed predictive models forecasting healthcare outcomes.
• Performed statistical analysis including regression, hypothesis testing, and clustering to extract insights and improve business strategies.
• Conducted data validation and quality assurance ensuring accuracy, consistency, and integrity of datasets.