Sayali – Business System Analyst IV/ Data Engineer – 10 years Exp – Our own H1B – Local to Bay Area CA – Willing to relocate anywhere in USA
| Consultant's Details: | Employer Details: |
| Consultant Name: Sayali M | Employer Name:Nextgen Technologies Inc |
| Work Visa: Our own H1B | Contact Person:Kushal Desai |
| Location: Bay Area,CA | Email:kushal.desai@nextgentechinc.com |
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Relocation: Yes – Willing to relocate
anywhere in USA
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Phone: +1 (413) 424-0484
Note: Please call after 09:00 AM PST
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Sayali's Resume
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PROFILE SUMMARY . |
Data Expert with 10+ years of experience delivering large-scale data migrations, cloud integrations, ETL/ELT pipelines, and enterprise data modeling across FinTech, SaaS, Infrastructure, and Energy. Expert in SQL, Python, Spark (PySpark), Databricks, Snowflake, GCP, AWS, dbt, Airflow, and modern BI ecosystems (Power BI, Tableau, Qlik Sense). Skilled at designing ingestion architectures, migrating ERP/CRM/HRIS systems, developing robust data lakes/warehouses, optimizing pipelines with Spark/Databricks, and building automated validation frameworks to ensure accuracy, lineage, and governance. Experienced bridging business, engineering, and cloud teams to deliver secure, scalable, production-grade data products that improve data quality, operational efficiency, planning accuracy, and executive decision-making.
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PROFESSIONAL EXPERIENCE SUMMARY . |
Business System Analyst IV/ Program Manager INTUIT Feb 2025 – present FinTech Senior Analyst in Technical Strategy and Planning team for Quickbooks and Turbotax, supporting executive financial (FP&A) planning through scalable data architecture, analytics, automation.
- Engineered cross-system ELT pipelines integrating Workday, ICIMS, and Salesforce into Snowflake via Databricks (PySpark +
Delta Lake), dbt, and GCP, increasing data accuracy by 40% and eliminating ingestion failures.
- Accomplished a 40% increase in data accuracy by building automated ELT pipelines migrating Workday, ICIMS, and Salesforce data into Snowflake via GCP + Databricks using PySpark, SQL, dbt.
- Increased cross-system data accuracy by 40% by engineering Databricks + GCP → Snowflake ELT pipelines unifying Workday, ICIMS, and Salesforce into governed financial models used for FP&A planning. (Databricks, PySpark, SQL, Snowflake, dbt, GCP)
- Improved forecasting, planning cycle time by 30% by automating dbt-driven ELT workflows with SQL + Python transformations, orchestration, enabling near real-time visibility for FP&A and Workforce Planning. (SQL, Python, dbt, Databricks, Snowflake)
- Strengthened enterprise-wide planning accuracy by 5–7% by aligning cost models, workforce metrics, expense drivers, and revenue components into a unified Snowflake financial data lake with enforceable RBAC controls. (Snowflake RBAC, dbt, Confluence)
- Enhanced data governance by 40% by implementing dbt schema tests, reconciliation checks, and lineage documentation across ERP/HRIS/CRM pipelines, reducing planning discrepancies and audit issues. (dbt tests, Databricks, SQL, GCP)
- Eliminated multi-system ingestion failures by deploying schema alignment rules, field mapping logic, and metadata-driven transformations for Workday, NetSuite, Oracle, and Salesforce migrations. (Python, SQL, Databricks)
- Enabled executive-level workforce and revenue reporting by consolidating 10+ enterprise systems into standardized models powering Qlik, Power BI, and planning dashboards. (Snowflake, SQL, Power BI, Qlik Sense)
- Resolved architecture conflicts across ERP, CRM, HRIS, and GCP by driving a single-source-of-truth design, improving data trust, lineage clarity, and financial planning consistency. (Databricks, Snowflake, Data Modeling)
- Improved auditability and GAAP-aligned reporting by 40% by designing governed financial data layers with dbt snapshots, SCD logic, and multi-domain reconciliation workflows. (dbt Snapshotting, SQL, Snowflake)
- Reduced enterprise reporting latency by 40% by converting spreadsheet-driven FP&A models into Snowflake + BigQuery SQL pipelines integrated with Qlik Sense dashboards. (SQL, BigQuery, Qlik Sense)
- Enhanced cross-functional planning accuracy by 5% by aligning cost models, project accounting metrics, and resource demand forecasts across FP&A, PMO, and Cost Accounting teams. (Power BI, DAX, Oracle ERP)
- Reduced enterprise financial reporting latency by 40% by engineering automated cross-system ELT pipelines integrating Workday
→ GCP → Snowflake, enabling real-time GAAP-compliant Financial Ops visibility. (Python, SQL, Snowflake, GCP)
- Resolved cross-system architecture conflicts during annual planning by driving alignment on a single-source-of-truth design integrating ERP, HRIS, CRM & data lake sources.
- Accelerated cloud adoption across Finance & Planning teams by creating process maps, RACI matrices, lineage documentation, and training materials for newly deployed Snowflake/ELT pipelines. (Confluence, Lucidchart)
Data Analyst/ FP&A Data Expert CHARGE EPC Jan 23 – Jan 2025 Worked on multiple infrastructure projects associated with the gas/electric giants for better decision making, business, operations & financial performance cross-functional teams. Part of the Planning/ Operations team.
- Reduced monthly financial discrepancies by 60% by redesigning cost & billing ETL pipelines and embedding anomaly detection aligned with GAAP variance & cost accounting rules. (Oracle ERP, SQL, Power BI, Python)
- Led end-to-end ERP migration (Foundation → Viewpoint Vista → SAP components) including schema mapping, transformation rules, and validation frameworks, reducing integration defects by 60%. (SQL, Python, ERP mapping tools)
- Built production-grade ETL pipelines for cost, billing, and project accounting datasets using SQL, Python, Power BI ingestion, and automated validations—reducing discrepancies by 60% across 1,000+ projects.
- Reduced monthly financial discrepancies by 60% by redesigning cost + billing ETL pipelines aligned to GAAP and cost accounting rules, implementing anomaly detection and automated reconciliations. (SQL, Python, Oracle ERP)
- Led end-to-end ERP migration with 60% defect reduction by engineering schema mapping, validation rules, and ingestion frameworks for Foundation → Viewpoint Vista → SAP components. (SQL, Python)
- Improved project cost visibility by 35% by developing standardized dashboards for burn rate, labor utilization, overhead, and revenue across 1,000+ projects. (Power BI, DAX, SQL)
- Accelerated month-end close by 3 days through ELT automation of WIP, cost, GL, and project controls data with governed KPI definitions. (SQL, Power BI, Oracle ERP)
- Established master data governance reducing mismatches by 30% by creating ingestion-ready schemas, dimension hierarchies, and validation automations across ERP + field systems. (SQL, dbt, Snowflake)
- Reduced client-impacting integration failures by 50% by diagnosing ingestion issues, API failures, schema drift, and transformation errors. (Python, SQL)
- Prepared cloud migration readiness by designing an AWS-aligned ingestion pattern (S3 → SQL pipelines) and metadata-driven transformations for ERP + operational systems. (AWS S3, SQL)
- Mentored interns/ junior analysts on SQL validations, dashboard design, ERP workflows, migration documentation. (SQL, Power BI)
- Delivered data stories and insight presentations to leadership, translating complex datasets into clear recommendations that influenced operational planning and metric definitions. (Power BI, Tableau, Snowflake)
- Enabled 5% improvement in project forecasting accuracy by developing portfolio-level models informing CFO’s capital allocation, cash flow scenarios, and investment decisions.
- Developed operational BI dashboards visualizing pipeline health, throughput, and KPI trends, enabling operations and leadership teams to make insight-driven decisions. (Power BI, SQL)
- Enhanced data integrity and reporting accuracy by engineering SQL-based validation frameworks that identified anomalies, reconciled mismatched records, and reduced data discrepancies by 60%. (SQL, dbt, Snowflake)
- Partnered with CFO, PMO, and cost accounting teams to define financial KPIs, standard costing templates, and reporting structures mapped to GAAP-compliant project accounting.
- Supported multi-million-dollar investment plans by delivering CFO-grade cost models, scenario analysis & ROI assessments.
Data Analyst B2U STORAGE SOLUTIONS May 2022 – Dec 2022
Second Life EV batteries are utilized to generate electricity which is sold for commercial use. Analyzed data to optimize performance and managed supply chain and inventory.
- Reduced asset breakdown costs by 25% by building real-time Power BI dashboards integrating IoT, ERP, and maintenance data to monitor asset health & cost drivers. (Power BI, DAX, SQL, Python)
- Integrated IoT sensor data, ERP, CRM, and asset systems into a unified cloud-based analytical model—similar to AWS/GCP pipeline architectures—reducing asset breakdown costs by 25%. (Python, SQL, Power BI)
- Reduced asset breakdown costs by 25% by integrating IoT sensor data with ERP + maintenance systems and building real-time asset health dashboards. (Power BI, DAX, SQL, Python)
- Improved forecasting accuracy by 20% by developing demand, sales, and maintenance prediction models tying cost-of-operations with supply chain metrics. (Python, SQL)
- Increased data reliability by diagnosing ingestion failures related to schema drift, timestamp mismatches, and null anomalies, stabilizing pipelines. (Python, SQL)
- Enhanced audit compliance by establishing governing metadata structures for SAP, Oracle, asset datasets with reconciliations, lineage.
- Reduced master-data inconsistencies by designing ingestion models for IoT + ERP data, enabling storage, real-time monitoring.
- Unlocked a 12% improvement in ROI by developing cost-benefit models for refurbish-vs-replace scenarios using asset depreciation + operational efficiency data. (Python, Excel)
- Strengthened reporting capabilities by building unified cloud-style analytical models similar to AWS/GCP architectures for asset health and throughput analysis. (SQL, Python)
Product Data Engineer/ FP&A Analyst INTELLECT DESIGN ARENA LTD. Dec 2017 – Sept 2020 Awarded for successful, on time and in full delivery of Fintech / banking payment processing product(SaaS) ’iPSH’ in iGTB and Insurance Fraud product ‘Xponent’ for established banks in North America.
- Improved transaction approval rates by 18% by analyzing payment processing data and optimizing fraud detection models for a
North American bank. (SQL, Python, Tableau)
- Reduced reporting latency by 45% in SaaS product analytics by developing automated GTM data pipelines integrating Salesforce, marketing platforms, and Snowflake. (SQL, Python, Snowflake)
- Integrated Salesforce + marketing systems + Snowflake to produce executive dashboards on revenue, LTV, GTM funnel economics.
- Improved fraud detection accuracy by 18% by analyzing payment processing data and optimizing approval-rate algorithms for a North American banking client. (SQL, Python, Tableau)
- Created KPI frameworks & automated reporting templates improving product team decision speed and Financial Ops visibility. Business Data Analyst(Marketing Analytics) GLOBUZZ MEDIA Jan 2016 – Dec 2017 Marketing startup analyst performing duties across Data, Digital Marketing Analytics, CRM,etc
- Built executive dashboards for campaign ROI & customer segmentation, improving digital strategy decisions by 30%. (Tableau, SQL)
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EDUCATION |
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California State University, EastBay |
Dec 2022 |
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University of Pune |
Dec 2017 |
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University of Pune |
Jun 2016 |
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SKILLS |
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ERP, CRM, HRIS Integration & Migration: Workday Financials, Oracle ERP, SAP, NetSuite, HCSS, ICIMS, Salesforce, Anaplan, Concur/Travel systems, Asset Tracking tools, ERP Role Design, SOD, SOX Controls, ITGC, Audit Readiness, UARs, GAAP Compliance Alignment, Metadata & Master Data Governance, Data Quality Diagnostics & Reconciliation, Schema Mapping, Databricks.
Analytics: GAAP Accounting Concepts, Financial Close Support, Variance Analysis, Standard Costing, Absorption Costing, WIP Tracking, Forecasting, Budgeting, Revenue Modeling, OPEX/CAPEX Modeling, Workforce Planning, Scenario Planning.
Data Engineering & Automation: SQL, Python(Pandas, NumPy, Scikit-learn), Snowflake, GCP, AWS, BigQuery, dbt, Airflow, Data Quality/Lineage, Data Warehousing, ETL/ELT, Metadata Automation.
Data Science & AI/ ML: AI-Assisted Analytics (LLM Querying, Automated Data Storytelling), Predictive Modeling & Feature Engineering
Cloud & Big Data: Hadoop, Spark, Hive, BigQuery (GCP), AWS, Azure.
Business Intelligence: Power BI, Tableau, Qlik Sense, Sigma, DAX, KPI Frameworks, Predictive Analytics, Anomaly Detection, Executive BI Dashboards (Product, Ops, Finance), Data Storytelling & Insight Communication.
Documentation & Enablement: SOPs, Process Maps, RACI Charts, Training Delivery, Confluence Documentation, Lucidchart, Audit Trail Design, Governance Frameworks.
Note: Please call between 09:00 AM PST to 06:00 PM PST
Kushal Desai
| 1735 N 1St ST., Suite 102 |San Jose, CA 95112
NextGen Technologies Inc
Email: kushal.desai@nextgentechinc.com. Website: www.nextgentechinc.com | +1 (413) 424-0484 |
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Sayali-NM-Resume-DE.docx