Karri Teja
Summary
Data Analyst experience in data analysis, validation, and transformation using SQL, Python, and data visualization tools such as Power BI and Tableau. Strong expertise in SQL and Python for data profiling, cleansing, and large-scale dataset analysis. Experienced in data mapping, reconciliation, and ETL processes to ensure accuracy between source and target systems. Skilled in performing data validation and quality checks to maintain data integrity and consistency. Hands-on experience in supporting User Acceptance Testing (UAT) and validating business reports. Proficient in exploratory data analysis (EDA) to identify trends, patterns, and anomalies. Experienced in building dashboards and reports using Power BI/Tableau for business insights. Strong ability to collaborate with stakeholders and translate business requirements into data solutions.
Overview
7
7
years of professional experience
Work History
Data Analyst
ICS Tech
12.2024 - Current
- Analyzed large datasets using SQL and Python to extract insights and support business decision-making.
- Performed data profiling, validation, and cleansing to ensure data accuracy and consistency across systems.
- Developed and maintained ETL pipelines for data transformation and reporting workflows.
- Conducted data reconciliation and comparison between source and target systems to identify discrepancies.
- Supported User Acceptance Testing (UAT) by validating datasets and ensuring alignment with business requirements.
- Collaborated with stakeholders to gather requirements and translate business needs into data solutions.
- Created dashboards and reports using Power BI to track KPIs and performance metrics.
- Performed exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
- Conducted statistical analysis to support business insights and reporting.
- Documented data workflows, validation rules, and transformation logic for audit and reporting purposes.
- Improved data accuracy and reporting efficiency by 15–20% through validation and reconciliation processes.
Data Analyst
MicroInfo
02.2024 - 11.2024
- Analyzed large datasets using SQL and Python to extract insights and support business decision-making.
- Performed data cleaning, preprocessing, and feature engineering to improve data quality for analysis and modeling.
- Performed statistical analysis and basic predictive analysis to support business decision-making.
- Conducted exploratory data analysis (EDA) to identify patterns, trends, and anomalies in datasets.
- Developed and optimized ETL pipelines to process and transform data from multiple sources.
- Performed data validation and quality checks to ensure accuracy and consistency across datasets.
- Created dashboards and reports using Power BI/Tableau to communicate insights to stakeholders.
- Collaborated with business teams to understand requirements and translate them into data solutions.
- Supported testing and validation of data outputs, ensuring alignment with business expectations.
- Improved model performance and data processing efficiency through optimization techniques.
Junior Data Analyst
AARMEC Technology
10.2019 - 06.2021
- Analyzed large-scale banking transaction datasets using SQL and Python to identify trends, inconsistencies, and data quality issues.
- Performed data profiling to detect missing values, duplicate records, and anomalies in customer and transaction data.
- Developed SQL queries to validate and reconcile data between source and reporting systems.
- Conducted data cleansing and transformation to improve data accuracy and consistency.
- Implemented data validation checks to ensure correctness of transaction records and balances.
- Compared datasets across multiple sources to identify data mismatches and discrepancies.
- Built interactive dashboards using Power BI to visualize transaction trends, KPIs, and potential fraud indicators.
- Collaborated with business stakeholders to validate data outputs and align with reporting requirements.
- Documented data flows, validation rules, and transformation logic for future reference and audit purposes.
- Improved overall data quality and reporting accuracy by ~15% through systematic validation and cleaning processes.
Education
Master’s - Information technology
Westcliff University
Bachelor of Technology - Electronics and Communication Engineering
GITAM University
Skills
- Languages: Python, SQL, R
- Data Analysis: Pandas, NumPy, Data Cleaning, EDA
- Data Validation: Data Profiling, Validation, Reconciliation
- ETL & Data: ETL Pipelines, Data Mapping, Data Modeling
- Visualization: Power BI, Tableau, Excel
- Databases: SQL (Azure SQL), NoSQL (basic)
- Cloud: Azure (Data Factory, Synapse, Databricks, Blob Storage)
- Tools: Git, GitHub, Azure DevOps
Timeline
Data Analyst
ICS Tech
12.2024 - Current
Data Analyst
MicroInfo
02.2024 - 11.2024
Junior Data Analyst
AARMEC Technology
10.2019 - 06.2021
Bachelor of Technology - Electronics and Communication Engineering
GITAM University
Master’s - Information technology
Westcliff University