Tarun Sachdeva

– Developed interactive dashboards in Power BI and Tableau to monitor sales performance, inventory trends, retention and operational KPIs, supporting ad-hoc business requests, improving reporting efficiency by 30% and reduced manual data preparation time by ~40% by centralizing business metrics. – Designed, build and maintained scalable ETL/ELT data pipelines using Synapse, MS-Fabric, Snowflake and Azure to Integrate data from various sources (operational systems, external partners, APIs, and SaaS solutions) into Azure Data Lake Storage Gen2, or central lake house / Warehouse ensuring high performance, schema evolution, and cost optimization to support analytics and reporting. – Ensured data governance and compliance in a regulated environment, with a strong focus on data privacy and security. Defined use cases, test scenarios, and managed UAT/PIV phases to validate that solutions met business and regulatory requirements. – Partnered with technical and business stakeholders to translate analytical needs into intuitive dashboards and reports. Conducted EDA to identify process improvement opportunities that improved operational efficiency by 15–20%. – Leveraged Al-powered tools such as Claude and ChatGPT to automate repetitive data tasks, streamline SQL query generation, and accelerate documentation and code development. Built Al-assisted workflows for data validation, pipeline debugging, and exploratory analysis, significantly reducing turnaround time for business requests. – Managed PMO and product development tasks using Jira, Confluence, and Rally, collaborating with cross-functional teams to enhance product and data initiatives following Agile, Scrum, and PI planning methodologies. Supported delivery planning and improved project tracking transparency.

– Designed and maintained Tableau & Power BI executive dashboards, management disclosures, and to visualize key risk KPIs, trends, and portfolio performance. Monitored Credit & Fraud Risk metrics including ECL (Expected Credit Loss), Accounts Receivable (AR), and Write-Off (WO), improving reporting efficiency by ~25%. Utilized SQL and Oracle to support data extraction and portfolio monitoring. – Produced detailed credit evaluation reports covering transaction behavior, financial risk indicators, and portfolio health. Developed and maintained data dictionaries documenting definitions, lineage, and data quality controls to support regulatory reporting aligned with IFRS9 and CECL frameworks (LGD, EAD, DPD), improving reporting governance standards. – Supported monitoring and validation of credit risk and underwriting models including PD and ECL models. Applied statistical analysis and machine learning techniques (Logistic Regression, Random Forest, Linear Models) to assess model stability and performance, contributing to improved model reliability.

– Gather data from various departments and tools, integrating it into a central data lake or warehouse along with optimizing the RDMS database.

– Actively participated in various automation projects, utilizing tools such as Power BI, SQL, Alteryx, and Python by automating the reporting in to BI Solution which results in 500 hours savings.