Manisha Sankalamaddi
Snowflake SnowPro Core Certified data professional with 3+ years of experience designing data pipelines, building cloud-based data warehouse solutions, and developing advanced SQL transformations for scalable analytics environments across Snowflake, AWS, and big data platforms.
Projects
Taxi HDFS to Snowflake Pipeline
Built an end-to-end NYC Taxi data pipeline using HDFS, PySpark, Snowflake, S3, and Streamlit. Ingested raw trip data, transformed it into analytics-ready datasets, loaded reference data from S3, and created reporting views.
AWS S3 to Snowflake Products Pipeline
AWS S3 to Snowflake data pipeline for product data ingestion, transformation, and task-based automation using storage integrations, external stages, raw staging tables, curated analytics tables, and scheduled refresh tasks.
GitHub Events Snowflake Pipeline
A free-access GitHub Events to Snowflake pipeline built with Python and Snowflake. Fetches GitHub event data through authenticated REST API calls, lands data as NDJSON, loads into RAW tables, and transforms into CURATED tables.
Streamlit Cortex Dashboard
Interactive Streamlit sales analytics dashboard built with Python and Snowflake, enhanced using Cortex Code CLI for prompt-driven code updates, UI improvements, and development acceleration.
Technical Skills
Snowflake
Snowflake Cloud Data Platform, Snowflake SQL, Stored Procedures, Streams, Tasks, External Stages, Zero-Copy Cloning, Incremental Loads, Query Optimization, Performance Tuning
Data Engineering & Warehousing
ETL/ELT, Data Migration, Data Transformation, Data Modeling, Dimensional Modeling, Star Schema, Data Warehousing, Data Validation, Data Reconciliation, Data Quality
Cloud Platforms & Big Data
AWS S3, AWS Glue, Amazon Redshift, Amazon Athena, GCP BigQuery, Hadoop, HDFS, Apache Spark, PySpark, Spark SQL
Programming, BI & DevOps
SQL, Python, Pandas, NumPy, Power BI, Tableau, KPI Reporting, Dashboard Development, Azure DevOps, Git, CI/CD, Docker, Kubernetes
Professional Experience
Data Analyst – Snowflake Developer — Integrated Proteins
- Designed and developed Snowflake-based ELT pipelines to migrate operational data from source systems into external stages, staging tables, and curated warehouse tables
- Built and maintained advanced Snowflake SQL stored procedures for data ingestion, transformation, business-rule processing, and recurring load execution
- Implemented incremental load workflows using Snowflake Streams and Tasks, enabling efficient processing of newly added and changed records
- Automated recurring data workflows through Snowflake Tasks with CRON scheduling for timely delivery of refreshed datasets
- Created reporting-ready Snowflake views and transformed data layers used as the backend for Power BI dashboards
- Used Zero-Copy Cloning for backup, testing, and environment replication, preserving production data integrity
- Performed data validation, reconciliation, deduplication, and query optimization in Snowflake
Data Analyst — Sodexo
- Built and maintained AWS-based data migration and transformation workflows using Amazon S3, AWS Glue, Amazon Redshift, and Athena
- Developed ETL pipelines to ingest raw data, apply transformations, and load structured datasets into Amazon Redshift
- Wrote advanced SQL queries in Redshift and Athena for transformation, reconciliation, validation, and trend analysis
- Used Python (Pandas, NumPy) to clean, standardize, preprocess, and automate recurring data preparation tasks
- Created and maintained curated reporting tables and analytical datasets that improved consistency of KPIs
- Supported incremental and scheduled data refresh workflows ensuring timely movement of updated data
- Applied strong data quality controls including source-to-target validation, reconciliation, and deduplication
Data Engineer — RSoft Systems & Services Pvt. Ltd.
- Ingested data from databases, flat files, APIs, and system-generated files into Hadoop/HDFS for centralized storage and distributed processing
- Built ingestion workflows using ETL jobs and Python scripts to land source data into raw HDFS layers
- Used PySpark and Spark SQL to read data from HDFS, clean and standardize fields, apply business rules, and transform raw data into structured datasets
- Processed both historical and incremental datasets in Hadoop and Spark, converting high-volume raw data into curated outputs
- Wrote Spark SQL and SQL-based logic for joins, aggregations, validation, reconciliation, and deduplication across large-scale datasets
- Moved transformed datasets from Hadoop/Spark layer into AWS including Amazon S3 for cloud-based analytics access
- Prepared curated datasets for downstream Power BI and Tableau reporting with strong data quality and consistency
Education & Certifications
Master of Science, Computer Science — University of Missouri–Kansas City
Certifications
- Snowflake SnowPro Core Certified (Credential ID: 179071720)