Data Engineer - Cloud Analytics &ETL Specialist
Resume:
B N S Likhitha
Dallas, TX +1-405-***-**** ***********@*****.*** www.linkedin.com/in/blikhitha0801
PROFESSIONAL SUMMARY
Data Analyst / Data Engineer with 5+ years of experience designing, developing, and optimizing scalable data pipelines and cloud-based analytics platforms.
Strong expertise in Python, SQL, AWS, Snowflake, Microsoft Fabric, Informatica ETL, and Power BI, delivering end-to-end data solutions from ingestion to visualization.
Proven ability to process and transform 10M+ daily records, reducing data processing time by up to 45% and improving reporting accuracy to 99%+.
Experienced in building enterprise data warehouses, implementing dimensional models, and delivering executive dashboards that drive data-driven decision-making.
Experience working in Linux/Unix environments with shell scripting to automate data workflows and improve ETL processing efficiency.
PROFESSIONAL EXPERIENCE
Amazon – Data Engineer
Dallas, TX Aug 2025 – Present
Architected and implemented AWS-based data pipelines (S3, Glue, Lambda, Redshift) processing 12M+ records daily, reducing batch processing time by 35%.
Designed and optimized Snowflake data warehouse, improving query performance by 40% using clustering keys and micro-partitioning strategies.
Implemented ETL workflows using Informatica PowerCenter, reducing manual processes by 55% and improving pipeline reliability.
Led migration of legacy reporting systems to Microsoft Fabric Lakehouse architecture, reducing reporting latency by 30%.
Developed advanced Power BI dashboards with DAX calculations, supporting 10+ business units and 200+ stakeholders.
Built automated data validation scripts in Python improving data quality and reducing reconciliation issues by 25%.
Implemented monitoring and alerting using AWS CloudWatch, reducing production incidents by 28%.
Tuned SQL queries and warehouse performance, lowering compute costs by 18% annually.
Mentored 3 junior analysts and conducted knowledge-sharing sessions on Snowflake optimization and ETL best practices.
Developed and maintained shell scripts for automating ETL processes, file handling, and job scheduling in Linux environments.
Managed and optimized data workflows in Unix/Linux systems ensuring efficient execution of batch jobs and data pipelines.
Bank of America – Data Engineer
Charlotte, NC, USA Nov 2023 – July 2025
Developed and maintained enterprise ETL pipelines using Informatica, processing 6TB+ financial data monthly.
Designed and implemented Snowflake data marts serving 150+ business users across compliance and finance teams.
Wrote complex SQL queries and stored procedures, reducing report generation time by 50%.
Automated transformation logic using Python (Pandas), saving 20+ hours monthly in manual effort.
Built AWS-based ingestion workflows integrating S3 and Redshift for scalable analytics.
Designed dimensional models (Star & Snowflake schemas) improving BI performance by 35%.
Improved regulatory reporting accuracy to 100% compliance standards through robust data validation checks.
Collaborated with cross-functional teams to gather requirements and translate them into scalable data solutions.
Reduced ETL job failures by 30% through enhanced error handling and monitoring mechanisms.
Developed complex SQL and PL/SQL queries and procedures in Oracle databases to support data transformation and reporting.
Worked extensively with Unix/Linux file systems, including file permissions, shell commands, and process management.
Enhanced ETL processes for data extraction, transformation, and loading into data warehouse systems, improving performance and reliability.
KPMG – Data Analyst
Bengaluru, India July 2022 – June 2023
Analyzed structured and semi-structured datasets using SQL and Snowflake for business intelligence reporting.
Developed advanced SQL queries across Snowflake and Oracle databases handling 1M+ customer records.
Automated weekly and monthly reports using Python scripting, reducing manual reporting effort by 40%.
Built interactive Power BI dashboards with DAX measures, improving executive visibility into KPIs.
Assisted in migration of on-premise databases to AWS cloud infrastructure, improving scalability by 45%.
Conducted data profiling and quality analysis improving reporting accuracy from 92% to 99%.
Performed trend and variance analysis contributing to 12% operational efficiency improvement.
Designed reusable data models to standardize reporting across departments.
Reduced ad-hoc data requests by 30% through self-service BI enablement.
Collaborated with engineering teams to optimize database performance and indexing strategies.
Tech Mahindra – Junior Data Analyst
Chennai, India Aug 2021 – June 2022
Created SQL queries and reports supporting 10+ business teams, improving turnaround time by 25%.
Assisted in ETL development using Informatica, reducing data loading errors by 35%.
Developed Power BI dashboards identifying sales performance gaps contributing to 8% revenue growth.
Supported Snowflake ingestion pipelines processing 2M+ daily transactions.
Performed data cleansing and validation improving data integrity by 20%.
Conducted root cause analysis for data discrepancies reducing recurring issues by 30%.
Assisted in database optimization reducing query execution time by 30%.
Documented ETL processes and data flows improving knowledge transfer and onboarding efficiency.
TECHNICAL SKILLS
Programming: Python (Pandas, NumPy), SQL, Shell Scripting
Cloud: AWS (S3, EC2, Lambda, Glue, CloudWatch)
Data Warehousing: Snowflake, Microsoft Fabric, Redshift
Operating Systems: Linux, Unix
ETL Tools: Informatica PowerCenter
Orchestration: Airflow
BI & Visualization: Power BI (DAX, Data Modeling)
Databases: Oracle, MySQL
Data Concepts: ETL, Data Modeling, Dimensional Modeling, Data Governance
Version Control: Git
CERTIFICATIONS
Google Cloud Certified: Professional Data Engineer
Microsoft Certified: Azure Data Fundamentals
Cognizant AI Virtual Experience Certification
EDUCATION
Oklahoma Christian University
Master’s in computer science Aug 2023 – May 2025
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