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About the role
As a Financial Systems and Data Engineer at KLDiscovery, you will sit at the intersection of financial systems, data engineering, advanced modeling, and strategic insight, operating with significant autonomy. The company is a $350M PE-backed organization currently undergoing a Quality of Earnings process and building towards a PE exit. The Finance function is being rebuilt from the ground up, including new planning platform (Pigment), new India data team, new AI agent infrastructure, and new KPI framework. Key Responsibilities: - Design and build Oracle Pigment data pipelines ensuring they are clean, automated, and reconciled daily. - Own data integrity across Oracle, Pigment, and Salesforce, identifying discrepancies before the US team's morning. - Automate manual report pulls such as SSRS AR reports, collections reports, and close checklists. - Administer Pigment/Adaptive platform including versioning, data refresh, user access, and API connections. - Co-develop AI agents with the US Sr. FP&A Analyst for various functions including Close, Rolling Forecast, Variance+Commentary, Strategy+Scenario, Investor Reporting, and Collections Intelligence. - Ensure data feeds for each agent are accurate as any discrepancies will impact the agent's outputs. - Operate, monitor, validate outputs of live agents, and continuously enhance prompt quality and accuracy. - Conduct financial modeling tasks such as 3+9 reforecast, scenario modeling, and capital/investment analysis. - Prepare one-page strategy memos for key decisions, develop KPI frameworks, and provide financial analysis for executive meetings. - Identify patterns in data to provide insights to the US team and prepare ELT pre-reads for executive meetings. Qualifications Required: - Four to six years of experience building integrated three-statement models in FP&A, consulting, banking, or PE. - Proficiency in Excel with dynamic models, scenario toggles, sensitivity tables, named ranges, and zero hardcoded assumptions. - Experience in building PE-grade deliverables in live contexts and utilizing Python, SQL, REST API, and LLM API for data pipelines and analysis. - Ability to translate complex financial analysis into a concise executive narrative and work directly with CFO- or PE-sponsor-level leadership. The company, KLDiscovery, provides technology-enabled services and software globally to help clients solve complex data challenges. They are committed to fostering an inclusive environment for all employees and promoting wellbeing and belonging. As a Financial Systems and Data Engineer at KLDiscovery, you will sit at the intersection of financial systems, data engineering, advanced modeling, and strategic insight, operating with significant autonomy. The company is a $350M PE-backed organization currently undergoing a Quality of Earnings process and building towards a PE exit. The Finance function is being rebuilt from the ground up, including new planning platform (Pigment), new India data team, new AI agent infrastructure, and new KPI framework. Key Responsibilities: - Design and build Oracle Pigment data pipelines ensuring they are clean, automated, and reconciled daily. - Own data integrity across Oracle, Pigment, and Salesforce, identifying discrepancies before the US team's morning. - Automate manual report pulls such as SSRS AR reports, collections reports, and close checklists. - Administer Pigment/Adaptive platform including versioning, data refresh, user access, and API connections. - Co-develop AI agents with the US Sr. FP&A Analyst for various functions including Close, Rolling Forecast, Variance+Commentary, Strategy+Scenario, Investor Reporting, and Collections Intelligence. - Ensure data feeds for each agent are accurate as any discrepancies will impact the agent's outputs. - Operate, monitor, validate outputs of live agents, and continuously enhance prompt quality and accuracy. - Conduct financial modeling tasks such as 3+9 reforecast, scenario modeling, and capital/investment analysis. - Prepare one-page strategy memos for key decisions, develop KPI frameworks, and provide financial analysis for executive meetings. - Identify patterns in data to provide insights to the US team and prepare ELT pre-reads for executive meetings. Qualifications Required: - Four to six years of experience building integrated three-statement models in FP&A, consulting, banking, or PE. - Proficiency in Excel with dynamic models, scenario toggles, sensitivity tables, named ranges, and zero hardcoded assumptions. - Experience in building PE-grade deliverables in live contexts and utilizing Python, SQL, REST API, and LLM API for data pipelines and analysis. - Ability to translate complex financial analysis into a concise executive narrative and work directly with CFO- or PE-sponsor-level leadership. The company, KLDiscovery, provides technology-enabled services and software globally to help clients solve complex data challenges. They are com
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