HARITHA PALIKA
Summary
Senior Data Engineer with 13+ years of experience in Data Architecture, Data Warehousing, ETL pipeline development, and cloud data platforms. Deep hands-on expertise in Snowflake — spanning schema design, performance tuning, data modeling (Star Schema, Data Vault), security (RLS/CLS), and end-to-end pipeline integrations with AWS and Azure. Proven track record of leading cross-functional teams, enforcing data governance standards, and aligning data architecture with business goals to deliver reliable, scalable analytics solutions.
Overview
14
14
years of professional experience
1
1
Certification
Work History
Sr. Data Engineer Lead
Intuit
Mountain View
03.2025 - 07.2025
- Led the design and delivery of a cloud-native analytics platform on AWS to support Intuit's financial product lines (TurboTax, QuickBooks). The project involved building scalable pipelines, optimizing Snowflake schemas for high-volume transactional data, and integrating dashboards for real-time business visibility.
- Designed and optimized Snowflake schemas for analytics covering millions of tax and financial transactions, applying clustering keys on date and product columns to achieve 40% faster query execution.
- Built ELT pipelines using AWS Glue that extracted raw transaction data from S3, transformed it with PySpark, and loaded it into Snowflake curated layers — reducing data latency from 4 hours to under 30 minutes.
- Implemented Snowflake Streams and Tasks to process incremental changes from source OLTP systems, ensuring near-real-time data availability in reporting tables.
- Enforced Column-Level Security using Dynamic Data Masking to protect taxpayer PII — SSNs and income figures were masked for all non-privileged roles while remaining fully accessible for compliance teams.
- Collaborated with QuickSight and Power BI teams to expose Snowflake tables via optimized views, enabling self-service analytics for 200+ business users.
- Led CI/CD automation for Snowflake schema deployments using GitHub Actions, reducing manual deployment errors and cutting release cycle time by 50%.
- Architected data governance policies including access control matrices, metadata tagging, and object ownership standards for the entire Snowflake environment.
Sr. Data Engineer Lead
Voya Financial
New York
07.2023 - 02.2025
- Spearheaded the migration of Voya's legacy on-premise financial data warehouse to a modern Snowflake + Azure Synapse architecture. This involved re-engineering data models using Data Vault 2.0, integrating AI/ML data pipelines, and establishing enterprise data governance standards for a Fortune 500 financial services company managing $700B+ in assets.
- Designed and implemented Data Vault 2.0 models in Snowflake — Hubs, Links, and Satellites — to provide a fully auditable, historized data layer for regulatory compliance and financial reporting.
- Migrated 15+ legacy Oracle and SQL Server data marts into Snowflake, re-engineering ETL logic in Azure Data Factory and Python, resulting in a 60% reduction in data processing time.
- Managed Snowflake multi-cluster virtual warehouse configuration to support concurrent workloads — dedicated warehouses for ETL, BI reporting, and AI/ML feature engineering without resource contention.
- Optimized heavy Snowflake queries used in end-of-day financial reconciliation — rewrote correlated subqueries into window functions and CTEs, cutting average runtime from 45 minutes to under 8 minutes.
- Implemented Snowflake Time Travel (90-day retention) to satisfy audit requirements, enabling the compliance team to query historical states of any financial table without restoring from backup.
- Developed CI/CD pipelines in Azure DevOps that automated Snowflake schema versioning, stored procedure deployments, and data quality gate validations before each release.
- Collaborated with AI/ML teams to provision clean, feature-engineered datasets in Snowflake for model training, applying row-level filtering to ensure models trained only on validated, compliant data.
- Enforced enterprise data governance by defining and publishing data standards, dictionary entries, lineage maps, and access policies — reducing data quality incidents by 45%.
- Mentored 4 junior data engineers on Snowflake best practices, SQL optimization, and DataOps workflows.
Data Engineer
HDFC Life
Mumbai
05.2017 - 06.2022
- Worked on building HDFC Life's cloud data platform on AWS, consolidating policyholder data, claims processing, and actuarial datasets into a unified Snowflake warehouse. The goal was to replace fragmented Excel-based reporting with governed, automated dashboards and improve underwriting analytics turnaround time.
- Led Snowflake schema migration from legacy Redshift environment, redesigning star-schema models for claims, policies, and agent performance data to improve query performance by 50%.
- Built automated ETL pipelines using AWS Glue and Lambda to ingest daily policy transaction files from S3 into Snowflake, replacing manual Excel uploads — reducing data preparation time from 3 days to 4 hours.
- Implemented Snowpipe for continuous loading of policyholder premium payment events into Snowflake, enabling real-time premium reconciliation dashboards for the finance team.
- Applied Dynamic Data Masking on Aadhaar numbers and medical history fields in Snowflake to comply with India's IRDAI data protection guidelines, ensuring sensitive data was never exposed to unauthorized analysts.
- Configured Snowflake resource monitors and query timeout policies to prevent runaway queries from overconsuming credits during peak actuarial reporting cycles.
- Conducted data quality checks using Snowflake stored procedures to validate record counts, referential integrity, and null thresholds before promoting data to the presentation layer.
- Collaborated with product teams and actuaries to define KPI definitions, metric hierarchies, and report-ready data mart structures, ensuring business alignment in all data models.
Data Analyst
Medikabazaar
Mumbai
08.2014 - 04.2017
- Supported the analytics function for India's largest B2B medical supplies marketplace, building sales and inventory dashboards, automating reporting pipelines, and providing data-driven insights to optimize supply chain operations and vendor relationships.
- Built Tableau dashboards tracking sales velocity, inventory turnover, and vendor fill rates, giving the procurement team actionable daily visibility into stock health.
- Developed Python automation scripts for ETL processes — extracting order data from MySQL, transforming business rules, and generating daily Excel/PDF reports, saving 10+ hours of manual work weekly.
- Managed Qlik Sense server environments including installation, patching, and user access administration for 80+ business users.
- Collaborated with cross-functional teams (sales, logistics, finance) to translate business requirements into data models and KPI definitions.
- Designed incremental data load strategies to optimize dashboard refresh performance, reducing reload times by 60%.
Data Analyst
Amway Corp
New Delhi
09.2011 - 07.2014
- Managed BI platform administration and reporting for Amway's India distribution network, supporting distributor performance tracking, regional sales analytics, and inventory management using QlikView and Qlik Sense.
- Managed QlikView and Qlik Sense server clusters across multiple regions, ensuring high availability for 150+ active BI users.
- Developed distributor performance dashboards with incremental load strategies, improving data refresh speed by 45%.
- Tuned QlikView data model performance by optimizing section access scripts, reducing RAM consumption and improving load times.
- Provided ongoing admin and production support — handled escalations, data anomalies, and report customization requests from regional sales teams.
Education
B.Tech - Computer Science & Engineering
P. Indra Reddy Memorial Engineering College (JNTU Hyderabad)
01.2011
Skills
- Snowflake
- Schema Design
- Data Vault
- Streams & Tasks
- Snowpipe
- Time Travel
- RBAC
- RLS
- CLS
- Dynamic Masking
- Query Profiler
- Virtual Warehouses
- Clustering Keys
- Materialized Views
- AWS
- S3
- Glue
- Lambda
- Redshift
- Athena
- QuickSight
- Azure
- Synapse
- Data Factory
- DevOps
- ML
- Star Schema
- Snowflake Schema
- Data Vault 20
- Conceptual Models
- Logical Models
- Physical Models
- ETL
- Pipelines
- Airflow
- Matillion
- PySpark
- Python
- Power BI
- Tableau
- Qlik Sense
- QlikView
- GitHub Actions
- Azure DevOps
- Jenkins
- Terraform
- Docker
- SQL
- R
- Metadata Management
- Data Lineage
- Access Control
- Audit Logging
- GDPR compliance
- IRDAI compliance
Certification
- Tableau Desktop Specialist
- SnowPro Advanced (Preferred)
- AWS Certified Data Engineer (In Progress)
Snowflake Core Expertise
Designed conceptual, logical, and physical data models using Star Schema, Snowflake Schema, and Data Vault 2.0 methodologies in Snowflake, Built multi-layer warehouse architectures (Raw, Staging, Curated/Presentation zones) to support enterprise analytics pipelines, Structured Snowflake databases with proper schema versioning and naming conventions for long-term maintainability, Built automated ETL/ELT pipelines loading data into Snowflake from AWS S3, Azure Blob Storage, and REST APIs, Used Snowflake Streams & Tasks for real-time CDC (Change Data Capture) to detect and process incremental data changes automatically, Integrated Snowflake with AWS Glue, Azure Data Factory, and Airflow for orchestrated, end-to-end data workflows, Leveraged Snowpipe for continuous, event-driven data ingestion from cloud storage into Snowflake tables, Optimized Snowflake query performance using clustering keys, materialized views, result caching, and partition pruning strategies, Right-sized virtual warehouses (XS to 4XL) and implemented auto-suspend/auto-resume to reduce compute costs by up to 35%, Identified slow-running queries via Query Profiler and EXPLAIN plans; rewrote SQL logic to reduce execution time significantly, Implemented Role-Based Access Control (RBAC) with hierarchical role structures to enforce least-privilege data access, Applied Row-Level Security (RLS) and Column-Level Security (CLS/Dynamic Data Masking) to protect sensitive financial and PII data, Configured Snowflake Time Travel and Fail-safe for point-in-time recovery and data backup compliance, Maintained audit logs, access history tracking, and data lineage metadata to meet regulatory and governance requirements, Managed user/role provisioning, warehouse scaling, and resource monitors to control costs and usage, Implemented CI/CD pipelines using GitHub Actions and Azure DevOps for automated Snowflake schema deployments, Used Terraform for infrastructure-as-code to provision and manage Snowflake environments consistently across dev/staging/prod
Timeline
Sr. Data Engineer Lead
Intuit
03.2025 - 07.2025
Sr. Data Engineer Lead
Voya Financial
07.2023 - 02.2025
Data Engineer
HDFC Life
05.2017 - 06.2022
Data Analyst
Medikabazaar
08.2014 - 04.2017
Data Analyst
Amway Corp
09.2011 - 07.2014
B.Tech - Computer Science & Engineering
P. Indra Reddy Memorial Engineering College (JNTU Hyderabad)