Data Engineer Computer Science

DIVYA KOLA

Data Engineer

Ohio, United States

Phone: 216-***-****

Email: ***********@*****.***

LinkedIn: www.linkedin.com/in/koladivya

EDUCATION

Campbellsville University • Kentucky, USA January 2023 – August 2024

Masters in computer science GPA: 4.0/4.0

Relevant Courses: Operating Systems, Database management System, Advanced Database Management,

Software Engineering, Cyber Security, Emerging Technologies, Cyber Law, Artificial Intelligence

Jawaharlal Nehru Technological University • Hyderabad, India June 2017– April 2020

Bachelor of Technology in Computer Science and Engineering GPA: 7.32/10

Relevant Courses: Object Oriented Programming (Java): Data Structures and Algorithms; Data Warehousing, Computer Networks, Web Technology, Software Development.

SKILL

Cloud Platforms : Amazon Web services (AWS)- EC2, S3, Lambda, Redshift, DynamoDB, AWS Glue

Programming Languages : Python (Pandas, NumPy), SQL

Data Transformation : Skilled in data cleansing, integration, aggregation, lineage, batch &real time ETL

processing

Data Warehousing and Databases: proficient in Redshift and DynamoDB for efficient data storage and analytics

ETL Tools : Expertise in AWS Glue for building scalable ETL workflows.

Data Analysis Reporting : Experienced in data profiling for insights and decision-making

Containerization and Orchestration: Hands-on experience with Docker for application deployment and orchestration

SQL : Advanced skills in writing optimized queries, stored procedures, data warehousing

solutions

WORK EXPERIENCE

Data Engineer January 2024 to December 2024

Client: Edward Jones, St.Louis

Designed and maintained scalable ETL pipelines to extract, transform, and load data from various sources, including flat files, databases, and APIs.

Developed ETL processes for staging data from multiple sources such as CSV, XML, and XLSX, ensuring efficient data integration.

Built and managed data lakes and warehouses on AWS S3 and Redshift to support advanced analytics and reporting needs.

Created ETL pipelines using AWS Glue to process S3 Parquet files in data lake environments.

Ability to perform SQL queries and light scripting to provide basic data analysis.

Secures information by completing database backups.

Monitor and maintain the performance and availability of data pipelines. Troubleshoot issues in the data pipelines and resolve problems with data ingestion, processing, and storage.

Maintains operations by following policies and procedures; reporting needed changes.

Developed custom data transformation and ETL workflows using Python-based AWS Lambda functions.

Utilized Python libraries such as Pandas and PySpark for data manipulation, cleaning, and analysis.

Optimized database systems with indexing, aggregation, and materialized views to enhance query performance.

Collaborated with data analysts and business users to gather requirements, deliver data solutions, and provide technical guidance.

Strong problem-solving skills and the ability to work independently and as part of a team.

Develop, test, and deploy ETL pipelines to move and transform data across multiple data sources.

Strong Knowledge in Python and object-oriented programming.

Experience working with AWS cloud services including S3, AWS Batch, ECR, Lambda, SNS, SQS, and other managed cloud platforms.

Updated data mapping documents to reflect actual development and ensure alignment with business goals.

Provide technical assistance to teammates as needed through collaboration and by sharing your expertise

AWS Data Engineer May 2020 – July 2022

Optus Infotech Pvt.Ltd, India

Extensive hands-on experience with AWS services, including EC2, S3, IAM, Lambda, Glue, SNS, Aurora, and DynamoDB.

Designed and implemented data pipelines using AWS Glue and Lambda to process and transform large-scale datasets.

Managed data lake architectures on S3 for efficient storage and retrieval of structured and unstructured data.

Developed database objects, including tables, views, and stored procedures, to support application-specific requirements.

Optimized query performance and managed databases using Amazon RDS and DynamoDB.

Integrated APIs and third-party data sources into AWS environments in collaboration with senior engineers.

Gathered and documented technical requirements, creating functional and technical design specifications.

Identify and pursue database enrichment and cleansing projects.

Create and present data-driven reports to executive leadership, supporting strategic decision-making

Initiative and passion to work independently.

Flexibility, strong decision-making skills, and effective time management skills.

Update documentation, reports, and maintain training materials associated with the Data Warehouse as well as Business Intelligence.

Gather requirements from clients, partners, and all internal departments via understanding their needs, challenges, and goals.

Designed and implemented ETL pipelines (SSIS, SQL Server, Snowflake) to enhance data infrastructure, supporting business insights and improving organizational strategy.

Built dimensional data models (Kimball, DVM) and optimized data workflows, improving business insights and enabling analytics for mental healthcare applications.

Led end-to-end data engineering projects, mentoring junior developers and ensuring adherence to best practices in ETL, data modeling, and organizational strategy.

Developed Power BI and Cognos dashboards, integrating data infrastructure with business intelligence solutions for mental healthcare analytics and strategic decision-making.

Collaborate with software developers and data scientists to deliver cross-departmental solutions.

Develop and support analysis of marketing campaigns.

Provide ad hoc analytical support to managers and departments as needed.

Engineering Trainee –Internship Jan 2020 – May 2020

Designed and developed an Emotion-Based Music Player leveraging Python, OpenCV, and TensorFlow for facial expression recognition.

Implemented a real-time emotion detection module to recommend mood-specific playlists using a curated music library.

Built a recommendation engine supported by a relational database (MySQL) for categorizing music by mood and genre.

Designed an intuitive user interface to enhance user experience, integrating features like play, pause, and dynamic playlist adaptation.

Optimized facial expression detection and music selection processes, reducing latency by 30%.

ACADEMIC PROJECTS & CERTIFICATIONS

Certificate on SQL - Completed Course by Demonstrating Theoretical and Practical Understanding of SQL

Certificate on Python

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