Padmashri Kokkalaki

Practical Database Engineer possessing in-depth knowledge of data manipulation techniques and computer programming paired with expertise in integrating and implementing new software packages and new products into system. Offering 4+ years background managing various aspects of development, design and delivery of database solutions. Tech-savvy and independent professional bringing outstanding communication and organizational abilities. A proven track record of working in a fast-paced environment. Worked on Apache Hive, Oozie, Informatica Intelligent Cloud Services (IICS), Oracle SQL, MS SQL, Azure Data Lake Storage, Azure Synapse, Azure Graph Explorer. Have been working in project which follow agile and scrum processes. Looking forward to working as Data Engineer, Microsoft Azure Engineer, ETL Developer, IICS Developer.

2021 Innovation & Delivery Excellence Award: For Outstanding Service Delivery to General Motors - Data & Analytics Factory Project
and Exemplifying IBM’s 1 Purpose – 3 Values – 9 Practices

Many appreciations emails, retrospective cards, bluepoints from Client and Team members for exceptional work on finishing many complex tasks on time.

• Actively participated in team building activities
• Hosted Cultural Event among the team.
• Provided excellent training to new joiners and freshers.
• Always got excellent reviews for being available all the time for all the team members (Development, QA or Production Support Team), being quick learner, on or before time completion of tasks.
• Excellent communication skills in English (spoken and written), Open-minded, independent problem-solver and highly motivated team player, Decision making, planning and leadership capabilities., Willingness to learn and adapt to new technologies and quick learning ability. Well trained to work with larger team sizes.

Training and Certification:

Advanced Program in Computational Data Science, IISC, March 2022 - 2023

· Sound knowledge of Machine Learning fundamentals

· Supervised Learning models known are Linear Regression, Logistic Regression, Decision Trees, Random Forest, Classification Modeling

· Unsupervised Learning models known Clustering.

· Knowledge of machine learning tools and libraries such as TensorFlow, Scikit-learn.

· Sound knowledge of exploratory data analysis to analyze and summarize datasets.

• Microsoft Azure Data Engineering: Completed training in Azure Synapse, Azure Databricks, Azure Data Lakes and Lakehouse, Azure Fabrics (In Progress).