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Technoidentity logo

Platform Analyst

Technoidentity
Posted 2 weeks ago
🌍Probably Worldwide🏠Remote📁Data & Analytics
Is this job info correct?

Job Description This is a remote position. Supercharge Your Career as a Financial Data Analyst at Technoidentity! Are you ready to solve data challenges that fuel business growth? At Technoidentity, we're a Data+AI product engineering company building cutting-edge solutions in the FinTech domain for over 15 years—and we're expanding globally. It's the perfect time to join our team of tech innovators and leave your mark! What’s in it for You? As a Financial Data Analyst, you will turn finance and accounting data into reliable reporting, dashboards, and decision-ready insight. This is an analytics-forward, techno-functional role sitting at the intersection of finance, accounting, analytics, and engineering. The pipelines and core platforms are already in place, so your focus is on defining the metrics that matter, validating data, building dashboards and reports, and partnering with stakeholders to drive decisions, rather than building data infrastructure from the ground up. What Will You Be Doing? Metrics and Reporting: Define, build, and maintain standardized financial and operational metrics, dashboards, and reports that leadership can rely on for decision making. Insight and Analysis: Extract, manipulate, and analyze large datasets to surface trends, anomalies, and actionable insights across finance and accounting workflows. Support ad hoc analysis to answer business questions quickly. Stakeholder Alignment: Serve as the main interface between finance, accounting, engineering, analytics, and business partners. Gather requirements, prioritize initiatives, translate complex data into accessible narratives, and manage stakeholder expectations. Data Quality and Governance: Validate assumptions, enforce data quality standards, and ensure reporting is accurate, consistent, and aligned with internal and regulatory requirements (e.g., SOX, GDPR, US GAAP). Platform Partnership: Partner with Engineering and data teams to shape source-of-truth data assets and standardized reporting structures (for example, fact tables for metric reporting), ensuring analyses draw from reliable, unified sources. Coordinate enhancements without owning pipeline construction. Close and Reporting Support: Support Accounting through monthly, quarterly, and year-end close cycles by delivering accurate reporting, reconciliations, and analysis, and by flagging issues that impact reporting reliability. Product and Project Management: Plan, scope, and execute reporting and analytics enhancements, migrations, and rollouts. Track progress, remove blockers, and ensure delivery on time. Work in a fast-paced continuous delivery agile model, attending daily standups and participating in sprint and iteration planning with Engineering. AI Enabled Analytics: Identify and apply AI and automation opportunities to accelerate analysis, reporting, and insight generation. Audit and Incident Support: Support audit readiness, documentation, and periodic reviews. Triage and communicate on reporting and data quality issues, partnering with Engineering for upstream resolution. Requirements What Makes You the Perfect Fit? An analytics-forward profile that pairs strong finance and business domain understanding with hands-on data analysis skills. Proficiency in SQL and experience working with large datasets. Strong experience with BI and visualization tools (for example, Tableau, Looker, or Mode) and advanced Excel. Familiarity with cloud data platforms (for example, Snowflake) and financial systems (for example, Oracle Fusion Financials or NetSuite). Solid understanding of financial reporting, accounting workflows, and the close process, with awareness of US GAAP and SOX. Excellent communication and storytelling skills, with the ability to present complex data clearly to leadership and cross-functional partners. A proactive mindset and genuine interest in applying AI to streamline finance and analytics operations. Bachelor's or Master's in a quantitative or related field (for example, Statistics, Economics, Finance, Computer Science, or Information Systems), or equivalent experience.

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