Data Engineer Power Bi

Manish Reddy Rajawala

+1-813-***-**** ****************@*****.*** LinkedIn

SUMMARY

Certified Data Engineer with 3+ years of experience designing scalable ETL pipelines, building cloud native data models, and integrating solutions across Azure, AWS, and Snowflake. Strong foundation in SQL, Python, and data warehousing, with proven success in automating workflows and improving data quality. Also brings 2+ years of experience delivering reporting solutions and business insights using tools like Tableau, Power BI, and Excel. Known for bridging data engineering with analytics to drive reliable, high-impact decision-making.

TECHNICAL SKILLS AND CERTIFICATIONS

Programming & Scripting: Python (Pandas, NumPy, PySpark), SQL (T-SQL, PL/SQL), Shell, VBA

Data Engineering & ETL: Azure Data Factory, AWS Glue, SSIS, Talend, dbt, Airflow, Power Automate, Snowflake Tasks

Cloud Platforms & Tools: Azure (Data Lake, Synapse, ADF), AWS (S3, Redshift, Lambda, EMR), Snowflake, Google BigQuery

Databases & Warehousing: SQL Server, Oracle, MySQL, Snowflake, Azure SQL, DB2, BigQuery, DynamoDB, MongoDB

Data Modeling & Pipeline Architecture: Star & Snowflake Schema, Dimensional Modeling, Data Vault, Data Lakehouse Design

Business Intelligence & Reporting: Power BI, Tableau, Looker, SSRS, Excel (VLOOKUP, VBA Macros, PivotTables, Power Query), Quicksight

Data Governance & Quality: Talend, Collibra, Data Catalog, Audit Trails, Data Profiling, Reconciliation Logic

Workflow, DevOps & Project Tools: Git, JIRA, Confluence, Agile/Scrum, SDLC, ServiceNow, Jenkins

Certifications: Microsoft Certified Power BI Data Analyst (PL-300), Cisco Certified Associate Python Programmer (PCAP)

PROFESSIONAL EXPERIENCE

Data Engineer – JSMN International Inc, Tampa, United States (JPMC) Sep 2024 – Present

Designed and implemented database backup and recovery procedures for SQL Server and Snowflake environments, supporting disaster recovery and data retention compliance.

Created data marts using star and snowflake schemas in Snowflake to support regulatory reporting, improving query performance and reducing report refresh times by 40%.

Designed and deployed interactive Power BI dashboards with DAX measures and dynamic filters, empowering 50+ users with real-time insights and cutting manual reporting hours by half.

Applied Lean Six Sigma techniques to streamline expense processes, yielding a 35% efficiency gain.

Automated SQL validation frameworks with audit trail logic, proactively detecting anomalies across 5+ enterprise systems and reducing QA escalations by 45%.

Designed and deployed scalable ETL pipelines using Azure Data Factory and Snowflake, reducing data load time by 40%.

Integrated ERP systems (SAP, Oracle, Workday) with centralized reporting layers, standardizing data inputs and reducing reconciliation errors by 30% through schema alignment and interface tuning.

Built clean, high-volume datasets to support AI/ML model training pipelines, enabling accurate prediction models and downstream analytics.

Data Engineer/Senior Analyst – Tata Consultancy Services, India (American Express) Dec 2019 – Jun 2022

Implemented data stewardship frameworks across 10+ domains, aligning business owners with data ownership responsibilities. Built dynamic reporting tools using Power BI and SSRS to improve visibility into compliance KPIs and reduce regulatory blind spots.

Developed end-to-end ETL pipelines using T-SQL, stored procedures, and Azure Data Factory to extract and transform multi-source datasets, reducing manual reporting time by 60% and increasing data reliability.

Processed semi-structured data (JSON, XML) from APIs and NoSQL sources like DynamoDB and MongoDB, integrating them into analytics pipelines.

Built automated data workflows using AWS Glue, Redshift, and S3 for batch ingestion and transformation, reducing manual intervention and accelerating data availability for analytics teams by 35%.

Engineered robust data validation workflows using dynamic T-SQL scripts and reconciliation logic, achieving 99.9% compliance with data integrity standards and improving audit-readiness.

Conducted fiscal variance root cause analysis using SQL and visual analytics, reducing forecasting errors by 15%.

Developed scalable ETL pipelines using Azure Data Factory and Azure Data Lake Storage to ingest, transform, and store enterprise data, improving data processing efficiency by 40% and enabling real-time reporting.

Drafted technical documentation and metadata repositories for all ETL jobs and dashboards, enhancing maintainability, audit traceability, and onboarding speed for new analysts.

Data Analyst – Accenture Aug 2017 – Dec 2019

Created automated Excel reports using Power Query, improving data refresh speeds and user adoption

Conducted end-to-end analysis of healthcare claims and member eligibility data to identify compliance issues, saving $250K+ annually in potential audit penalties.

Utilized Excel (VLOOKUP, Pivot Tables, Power Query) for data manipulation and reporting automation.

Built SQL logic for trend, cohort, and compliance analytics using window functions and CTEs.

Collaborated cross-functionally to refine KPIs and improve sprint efficiency, increasing task velocity by 25%.

Integrated Power BI and Tableau dashboards with live datasets, automating insights delivery and cutting ad-hoc reporting volume by 30%.

Created ad-hoc reports to address custom stakeholder requests, improving data-driven decision-making efficiency by 20%.

ACADEMIC PROJECTS

Healthcare Utilization Analysis: Mar 2023

Analyzed hospital datasets to identify trends in procedure frequency, leading to a 20% reduction in unnecessary procedures and optimized allocation of medical resources.

Built predictive models using historical patient data to forecast admission rates with 85% accuracy, improving hospital capacity planning.

Insurance Claims Analysis: Oct 2023

Conducted comprehensive data analysis on insurance claims to detect anomalies and fraudulent patterns, resulting in a 15% reduction in fraudulent claims.

Applied machine learning techniques to develop a predictive model that forecasted claim volumes with 90% accuracy, aiding in proactive resource allocation.

EDUCATION

The University of Tampa, Florida, United States Aug 2022 – May 2024

Master of Science – Information Technology & Management

Osmania University Aug 2017

Bachelors – Business Administration in Financial Accounting

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