Nov 2024 – Nov 2025 · 1 yr

• Led enterprise-wide data architecture and pipelines for 2.3M employees across 8 countries, aligning HCM systems with analytics, payroll, and benefits.
• Designed and deployed 12+ Workday EIB integrations for automated onboarding, offboarding, and compensation updates; implemented validation rules and business-process triggers to achieve 99.8% data accuracy.
• Built Workday → BigQuery CDC pipeline using Workday Event Subscription Service and Kafka, processing 500K+ daily events with automated reconciliation and <5-minute discrepancy detection.
• Architected a Workday–Big Data Lake reconciliation system validating 2.3M+ daily employee records; reduced manual effort by 95% and BigQuery costs by 90%.
• Architected cloud-native ETL processing 7.5M Salesforce records (1,079 columns), delivering 60% storage savings and a 95% reduction in data transfer.
• Designed containerized microservices and RESTful APIs aligned with SOA principles.
• Implemented automated deployments, OAuth2 authentication, CDC, and high-uptime CI/CD pipelines using Looper, Jenkins, and Docker.
• Partnered with HR data scientists and product teams to lead enterprise-wide overhaul and automation initiatives, delivering measurable business impact.

Nov 2022 – Nov 2024 · 2 yrs

• Led enterprise-scale data initiatives across payroll automation, data quality, and dashboarding using Apache Spark, Scala, Python, Airflow/Astronomer, BigQuery, and SAP SLT Streaming.
• Payroll Compare Testing Automation
• Built a scalable ETL system comparing payroll data for 1.7M employees across platforms, saving $1.1M annually and reducing execution time by 87%. Integrated Spark, Scala, Python, GCS, Hive, and BigQuery.
• SAP Payroll Report Transformation
• Architected a reusable framework to parse and normalize 150+ unstructured SAP reports using regex and self-service ingestion, enabling advanced analytics and reducing manual effort.
• Data Quality Automation & Certification
• Led a cross-functional effort certifying 350+ tables in one quarter. Built a YAML-based automation tool for DQ rule execution, enabling onboarding of 1800+ datasets and cutting execution time by 45%.
• Application Total Cost of Ownership Project:
• Delivered automated dashboards for pre/post-load validation across 6 models, 35 tables, and 300 attributes—reducing validation effort by 80% and improving SLA turnaround by 66%.
• Perfect Autopay US Dashboard
• Designed and launched a payroll tracking pipeline in under a week to detect defects and minimize over/underpayments.
• Tech Stack:
• Python, Scala, Apache Spark, HDFS, Hive, Airflow/Astronomer, GCS Buckets, BigQuery, SAP SLT Streaming, Shell, Docker, Kubernetes, JIRA, Scrum, Architecture Design Reviews, Data Modeling

Jan 2022 – Nov 2022 · 10 mos · Jersey City, New Jersey, United States · Remote

• Led the end-to-end implementation of a data pipeline for a SaaS-based internal communications tool, enhancing the efficiency of mass messaging for the Corporate Communications team.
• Captured and finalized project requirements, designed scalable processes, and supervised development activities.
• Collaborated with technical leads to resolve complex challenges, ensuring on-time delivery and adherence to project milestones.
• Maintained continuous stakeholder engagement, addressing queries and aligning technical execution with business needs.
• Prevented a potential $100K annual financial impact by enabling successful deployment and usage of the SaaS platform.
• Proactively mitigated risks and avoided timeline disruptions, streamlining execution and reducing rework.
• Tech Stack:
• GCS Buckets, HDFS, Python, Scala, Apache Spark, Shell, Airflow/Astronomer, BigQuery, Docker, Kubernetes

Jul 2020 – Jan 2021 · 6 mos · Milpitas, California, United States · Remote

• Collected, analyzed, and shared data to drive improvements in key business metrics, customer experience, and overall business performance.
• Designed, developed, and tested comprehensive BI solutions including databases, data warehouses, queries, views, reports, and dashboards.
• Built and evaluated innovative BI tools and automated reporting systems using web and database technologies.
• Executed data conversions, imports, and exports across internal and external software systems to ensure seamless data flow.
• Integrated BI platforms with enterprise applications, enhancing accessibility and usability across teams.
• Improved BI tool performance by implementing optimized data filters and indexes, resulting in faster and more reliable insights.
• Documented new and existing models, solutions, and implementations to support scalability and maintainability.
• Tech Stack:
• Python, Tableau, Snowflake, Jira

Oct 2019 – Jan 2020 · 3 mos · Gurugram, Haryana, India · On-site

• Led the architecture and development of a real-time dashboard for the CEO of State Bank of India Credit Cards, delivering actionable insights to support strategic decision-making.
• Conducted stakeholder interviews to capture business requirements and authored detailed technical specifications.
• Designed and implemented a scalable dashboard architecture to monitor key performance indicators (KPIs) including:
• Platform-wise expenditure trends
• Geographic distribution of customer sourcing for new accounts
• Hourly and daily agent performance tracking
• Ensured high availability and responsiveness of the dashboard through real-time data integration and monitoring.
• Tech Stack:
• Python, InfluxDB, Grafana, Prometheus

Jan 2019 – Oct 2019 · 9 mos · Gurgaon, India

• Geospatial Data Warehousing & Security Monitoring
• Designed and implemented the destination data warehouse architecture to store and process geospatial data in cloud environments.
• Developed preprocessing scripts and workflows to migrate data from legacy database servers to cloud-based platforms, enabling seamless daily and weekly data ingestion.
• Defined key metrics and conducted a cost-benefit analysis across multiple cloud data warehouses (e.g., Snowflake, Redshift) to align with stakeholder requirements.
• Set up a log collection and real-time alerting system using Splunk for a U.S.-based insurance client, aggregating logs from Azure Cloud, MS Office, and virtual machines to detect and respond to suspicious activity.
• Enhanced data reliability and system performance through optimized workflows and proactive monitoring.
• Tech Stack:
• AWS EC2, S3, Talend, Alteryx, Hadoop, Snowflake, Redshift, MS SQL Server, Splunk, MapReduce

Feb 2017 – Jan 2019 · 1 yr 11 mos · Gurgaon, India

• Data Integration & Reporting for Transactional Systems
• Collaborated with clients and vendors to gather business requirements and authored comprehensive technical specifications for daily transactional data consumption.
• Designed and developed ETL workflows to ingest and normalize data into a centralized data warehouse.
• Built data pipelines to transfer information from the warehouse to reporting databases and data lakes, supporting diverse analytics needs.
• Created custom reporting interfaces and KPIs, delivering tailored reports for stakeholders at multiple organizational levels.
• As part of managed services, implemented data quality checks and validations to ensure consistent and reliable execution of daily workflows.
• Tech Stack:
• MS SQL Server, Talend, Python, SFTP, Power BI

Jun 2016 – Feb 2017 · 8 mos · Noida, Uttar Pradesh, India

• Preferred Number Service (PNS) to Buyer Intent Generation
• Technologies: PHP, Oracle, cURL
• Led the redesign of IndiaMART’s Preferred Number Service (PNS), enhancing the buyer-supplier call connection system for improved reliability and data capture.
• Architected a new data ingestion pipeline to extract comprehensive metadata from PNS call instances and store it in a centralized data lake for downstream analytics.
• Collaborated with external calling service vendors to design and implement a real-time, single-point API for continuous data exchange.
• Developed robust data migration scripts to filter, validate, and transfer clean datasets from the data lake to the calling service database.
• Conducted extensive testing of APIs and migration scripts across diverse data scenarios to ensure fault tolerance and data integrity.