Mary Nikhitha Gode

• Designed, developed, and maintained cloud-native data pipelines to ingest, transform, and validate structured and semi-structured data from internal systems and external APIs. • Built and maintained analytical data models and tables in Snowflake to support business reporting, analytics, and operational use cases. • Developed and maintained ETL/ELT workflows using Python, SQL, and dbt to standardize and curate data for downstream analytics. • Managed cloud-based data storage and processing workflows using AWS services, including S3, Glue, and Lambda. • Implemented data quality checks, validation rules, and monitoring to ensure data accuracy, reliability, and consistency. • Investigated and resolved data discrepancies, pipeline failures, and performance issues in production workflows. • Collaborated with data analysts, product managers, and business stakeholders to gather requirements and deliver curated datasets. • Participated in code reviews, maintained technical documentation, and supported access controls and infrastructure configuration using Terraform and GitHub.

• Analyzed business and operational processes to identify inefficiencies and data-driven improvement opportunities. • Designed and implemented ETL pipelines to support analytics, reporting, and operational decision-making. • Extracted, cleaned, transformed, and analyzed data from relational and NoSQL databases. • Developed analytical reports and presentations to communicate insights to technical and non-technical stakeholders. • Documented data workflows, analytical logic, and process improvements for maintainability and knowledge transfer. • Supported ongoing optimization initiatives using data analysis and automation techniques.

• Designed, developed, and maintained data pipelines and analytical workflows to support business reporting and decision-making. • Extracted data from multiple structured and semi-structured sources and transformed it using SQL and Python for analytics consumption. • Built and optimized SQL queries and data transformations to support KPI tracking, trend analysis, and performance monitoring. • Designed scalable data models and assisted in maintaining cloud-based data warehouses. • Implemented data validation and reconciliation checks to ensure source-to-target accuracy and data quality. • Collaborated with business stakeholders to translate reporting requirements into technical data solutions. • Supported automation of recurring ETL workflows and documented data processes and schemas.

• Developed and optimized SQL queries and data models to improve data retrieval performance and reporting efficiency. • Conducted customer behavior and sales data analysis to deliver actionable insights for business and marketing teams. • Collaborated with development and data engineering teams to support and refine ETL workflows. • Built and maintained dashboards and reports using business intelligence tools for management decision-making. • Performed data cleansing, validation, and quality checks to resolve inconsistencies in analytics pipelines. • Assisted in predictive analytics initiatives by preparing datasets and supporting forecasting models. • Automated portions of data workflows to improve efficiency and reliability.

Designed and optimized data models to improve storage efficiency and query performance. • Developed and refined ETL processes to integrate data from multiple structured sources into centralized data warehouses. • Performed data cleansing, transformation, validation, and profiling to resolve data quality issues. • Built and optimized SQL queries for large datasets to support reporting and ad-hoc analysis. • Created dashboards and visualizations using BI tools to present insights to management. • Assisted in predictive analytics and sales forecasting initiatives using Python and cloud-based tools. • Collaborated with data engineers to troubleshoot pipeline performance issues and support scalable analytics solutions.