Data Engineer Azure

VENKATA VIJAYA RAJA TEKI

JUNIOR DATA ENGINEER

**********@*****.*** 630-***-**** CHICAGO HE/HIM

PROFILE

Detail-oriented Data Engineer with a Master’s in Data Science and hands-on experience in data transformation, scripting, and cloud-based ETL pipelines. Skilled in PowerShell, Python, SQL, and Azure Data Factory, with exposure to API integration, automation, and financial data handling. Adept at building scalable data workflows, transforming raw inputs into actionable insights, and ensuring data quality across systems. Seeking to leverage my skills in a dynamic team as a Data Transformation Analyst. SKILLS

•Scripting & Programming: PowerShell, Python (Pandas, NumPy), SQL

•Data Engineering & ETL: ADF, Azure Synapse Analytics, Azure Data Lake, Azure IoT Hub, APIs, Flat Files

•Data Transformation & Integration: ETL Pipelines, Data Cleaning, Liquid Templating (learning), REST API

(basic knowledge)

•Data Visualization: Power BI, Tableau

•Cloud Platforms: Microsoft Azure (ADF, Synapse, Blob Storage, Functions)

•Other Tools: Azure DevOps, SSRS (exposure), Documentation, Microsoft Excel PROFESSIONAL EXPERIENCE

Junior Data Engineer

L & T Technology Services

•Designed and implemented data transformation workflows using Python and PowerShell scripts, automating the ingestion of structured and unstructured data from IoT edge devices, flat files, and REST APIs.

07/2020 – 11/2022

Bengaluru

•Developed and maintained ETL pipelines using Azure Data Factory, ensuring efficient data flow from external sources into Azure Data Lake Storage and Azure Synapse Analytics.

•Built custom API integrations to automate data exchange between client systems and cloud platforms, reducing manual effort and improving data consistency.

•Conducted data mapping and profiling activities to transform financial and sensor data for use in real-time dashboards and analytics.

•Documented transformation logic, developed reusable components, and collaborated closely with business stakeholders and data analysts to gather data requirements and implement tailored solutions.

•Created validation scripts and automated reconciliation checks to ensure data quality, accuracy, and consistency across systems.

•Participated in designing scalable cloud data architecture to support real-time telemetry and streaming analytics using Azure IoT Hub and Event Hubs.

•Enabled reporting and visualization by preparing curated datasets for Power BI dashboards, supporting operational and strategic decisions.

•Troubleshot pipeline issues, implemented logging and alerting mechanisms, and ensured compliance with best practices for data security and reliability. Key Technologies:Azure Data Factory, PowerShell, Python, REST APIs, Azure Data Lake, Azure Synapse, Azure IoT Hub, JSON/XML, Power BI, SQL PROJECTS

Sales Data Pipeline on Azure

• Built end-to-end ETL pipelines using Azure Data Factory to ingest sales data from multiple sources into Azure Data Lake Storage.

• Transformed raw data using Azure Databricks and PySpark for clean and structured analytics-ready datasets.

• Created and managed data storage and processing workflows leveraging Azure Synapse Analytics.

• Automated data validation and monitoring to ensure data accuracy and pipeline reliability. Predicting Car Insurance Claims Using Machine Learning: Enhancing Risk Assessment and Policy Optimization

• To predict car insurance claims by analysis customer demographics and driving Behaviour. It aims to enhance risk assessment and optimize policy customization using Machine Learning models.

• This project involves Three Steps to analyse the dataset and predict claims Data Cleaning, K-Nearest Neighbors

(KNN) and Decision Tree.

• Data was pre-processed to handle missing values and encode categorical values, Models were trained and evaluated to identify the best-performance algorithm for claim prediction

• KNN achieved FLAWLESS performance in classification also it is the best model for predicting insurance claims where as Decision Tree provided interpretable insights despite slightly lower accuracy. EDUCATION

Masters in Data Science

Lewis University

•Proficiency in analyzing complex data sets using tools like SQL, Python, R, Machine Learning and Data visualization platforms such as Power BI and Tableau. 03/2023 – 12/2024

Romeoville, Illinois

• Understanding of how to transform data into actionable insights, employing business intelligence tools and techniques to drive strategic decision-making. Bachelor of Technology in Mechanical Engineering

Amrita Vishwa Vidyapeetham

Major in Mechanical Engineering with efficient knowledge of analyze sensor data from machines, predict equipment failures, and optimize maintenance schedules, reducing downtime and costs.

07/2018 – 03/2022

Coimbatore, India

CERTIFICATES

•Microsoft Certified: Azure

Fundamentals

•SQL for Data Analysts – Udemy

•Power BI – Intermediate

Certification

ADDITIONAL INFO

•Familiarity with financial datasets and automation practices

•Learning Liquid templating and expanding PowerShell scripting

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