Data Analytics Engineer with SQL/Python

Shamitha Reddy

+1-940-***-**** ****************@*****.***

PROFESSIONAL SUMMARY

Data professional with experience analyzing customer behavior, sales performance, and marketplace trends using SQL and Python. Developed and maintained Tableau and Power BI dashboards, automated reporting processes, and managed data integrations to deliver actionable insights. Skilled in complex SQL querying, advanced Excel analysis, data validation, and CRM data loading, seeking to support marketing performance measurement and audience segmentation. TECHNICAL SKILLS

• Cloud Platforms: Amazon S3, AWS Glue, Lambda, Athena, Redshift, CloudWatch, IAM, EC2, EventBridge, Step Functions Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Databricks, SQL Database, Synapse Analytics, Blob Storage, Key Vault

• Programming Languages: Python, SQL, PySpark, Shell Scripting

• Big Data & Distributed Processing: Apache Spark, PySpark, Databricks, Spark SQL, Delta Lake

• Databases & Data Warehousing: SQL Server, PostgreSQL, MySQL, Snowflake, Amazon Redshift, Azure SQL Database

• ETL / ELT & Data Integration: AWS Glue, Azure Data Factory, ETL/ELT Pipelines, Data Ingestion, Data Validation, Data Transformation, Data Cleansing, Incremental Loading, CRM Systems, Marketing Automation

• Data Modeling & Warehousing: Dimensional Modeling, Star Schema, Snowflake Schema, Fact & Dimension Tables, Data Warehousing, Data Marts

• Reporting & Analytics: Power BI, Tableau, Microsoft Excel, Dashboard Development, KPI Reporting, Data Visualization, Ad Hoc Analysis, Business Intelligence, Data Analysis, Marketing Analytics, Customer Segmentation

• AI & Advanced Analytics: Feature Engineering, Data Preparation for Machine Learning, Predictive Analytics Support, AI-Ready Data Pipelines, Statistical Analysis

• DevOps & Collaboration Tools: Git, GitHub, Jira, CI/CD, Agile Scrum, Code Reviews

• Data Quality & Governance: Data Profiling, Data Quality Validation, Metadata Management, Data Lineage, Data Governance Standards

PROFESSIONAL EXPERIENCE

Wells Fargo Jan 2025 - Present

Data Engineer

• Build scalable ETL pipelines using Azure Data Factory, Python, SQL, and PySpark to process enterprise banking data, improving data availability for reporting and analytics consumption.

• Develop ingestion workflows using Azure Data Lake Storage, Data Factory and event-driven integrations to consolidate structured and semi-structured datasets into centralized repositories supporting business reporting.

• Create PySpark transformation jobs in Databricks standardizing customer, transaction, operational data while implementing validation frameworks, improving consistency across analytics platforms, regulatory reporting.

• Optimize SQL queries and Azure Synapse Analytics workloads, improving reporting responsiveness by 30%, while enabling business users to access trusted datasets for operational decisions.

• Implement automated data quality checks using Python and SQL to identify anomalies, validate records, enforce governance standards, and maintain reliable enterprise datasets.

• Monitor production pipelines using Azure Monitor and troubleshooting tools while partnering with application teams to resolve source data issues and maintain data integrity.

• Develop reusable Azure Data Factory pipelines and standardized ingestion frameworks, reducing onboarding effort for new source systems by 25% while improving maintainability.

• Support near real-time processing initiatives by integrating event-driven data feeds and building curated datasets for AI and machine learning readiness across platforms.

• Automate recurring data preparation activities using Python scripts, reducing manual effort by 25% while improving operational efficiency and consistency across workflows.

• Implement metadata standards, business documentation, and lineage practices improving visibility into pipeline dependencies, data definitions, governance requirements, and downstream consumption.

• Perform source-to-target validation using Apache Spark and Snowflake, support release activities, and contribute to Agile sprint planning, backlog refinement, code reviews, and production support, ensuring data accuracy and on-time delivery for forecasting reports

• Maintain Git version-controlled repositories and optimize workflow execution through tuning techniques, reducing processing times by 30% while supporting forecasting and reporting. johnson & Johnson Jan 2022 - Dec 2023

Data Engineer

• Developed AWS Glue pipelines ingesting healthcare and operational datasets from internal and external sources into Amazon S3, supporting enterprise analytics and reporting requirements.

• Built PySpark workflows on AWS Glue and Amazon EMR to cleanse, standardize, enrich, and transform large-scale business datasets while improving reporting consistency.

• Implemented incremental loading strategies using AWS services, improving pipeline efficiency by 20% through reduced unnecessary processing while maintaining reliable and timely data availability.

• Created SQL-based validation frameworks and integrated data from APIs, relational databases, and flat files, ensuring completeness, accuracy, consistency, and trusted reporting outcomes.

• Designed reusable ETL components and automated processing activities using Python, AWS Glue, and Lambda, reducing development effort while accelerating onboarding of new sources.

• Supported Power BI initiatives by developing curated datasets and data models in Snowflake and Azure Data Lake Storage, and created KPI-driven reports that enabled healthcare teams to make faster operational decisions

• Collaborated with analysts, business stakeholders, and application teams to gather requirements, define transformation rules, implement governance standards, maintain comprehensive documentation practices effectively.

• Built feature-ready data preparation workflows supporting machine learning and predictive analytics initiatives while enhancing pipeline stability through monitoring, controls, and exception handling.

• Performed SQL tuning, resolved production issues, and delivered Agile enhancements, improving dashboard responsiveness by 25% while supporting releases and project milestones.

eBay Mar 2021 - Dec 2021

Data Analyst

• Performed customer segmentation and analyzed behavior, sales performance, and marketplace trends using SQL and Python, delivering actionable insights that supported business decisions and strategic planning.

• Developed business intelligence dashboards in Tableau and Power BI, KPI scorecards, and visualization solutions providing stakeholders with enhanced visibility into business performance and marketplace metrics.

• Extracted, transformed, and loaded campaign data into CRM systems using SQL, supporting ad hoc analysis, recurring reporting requirements, and reliable data-driven decision making.

• Conducted data validation, reconciliation, and root cause analysis activities, ensuring reporting accuracy, resolving discrepancies, and maintaining consistency across enterprise reporting outputs.

• Worked with product, operations, and business teams to perform statistical analysis and document reporting specifications, building Power BI dashboards that delivered timely insights and sped up decision-making.

• Created automated reporting solutions using SQL and Microsoft Excel (including pivot tables and lookups), reducing recurring manual reporting effort by 30% while improving reporting efficiency.

• Developed reusable SQL scripts, supported A/B testing initiatives, prepared analytical datasets, and validated business outcomes to strengthen reporting reliability and decision-making.

• Assisted with data cleansing, enrichment, and monthly performance reporting activities, improving data quality, usability, and stakeholder confidence in reporting deliverables consistently.

• Leveraged marketing analytics to optimize campaign performance by tracking key metrics and providing recommendations to marketing teams.

CERTIFICATIONS

• AWS Certified Machine Learning Engineer – Associate

• AWS Certified Developer – Associate

EDUCATIONAL DETAILS

University of North Texas

Master of Science, Data Science

MLR Institute of Technology

Bachelor of Technology,Computer Science

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