Deepika Ramaraj

About Deepika Ramaraj

Ever since I dove headfirst into the world of data, it\'s been a thrilling journey of discovery. I have always found joy in untangling complex data sets and transforming them into meaningful, actionable insights. Throughout my career, I\'ve been fortunate enough to work with a variety of organizations, big and small, and apply my skills to a wide spectrum of challenges.Back in the days at Infosys, I spearheaded the development of a new data processing pipeline that improved processing speed by 35%. My team and I were able to dramatically decrease the time it took to analyze data, which in turn allowed us to make faster, data-driven decisions. I also assisted in training over 30 staff members on data management best practices, which had a significant impact on efficiency.One of my proudest moments was at ZS Associates, where I designed a data architecture that reduced storage costs by 25%. It was here that I learned the importance of understanding business needs and translating them into practical, cost-effective data solutions. If you\'re in need of someone who can turn your data into a strategic asset, feel free to reach out to me via email. I\'m always open to new opportunities and love connecting with new people. Skills: Extract, Transform, Load (ETL), Data Engineering, Apache Spark, Data Warehousing, Azure, Reporting (Power BI)

Experience

1. Technology Consultant Data & Ai

   Microsoft

   Apr 2024 — Present · Bengaluru, IN

   Led the design and implementation of a metadata-driven ADF pipeline processing 2M+ records daily from diverse sources, including PostgreSQL, Cassandra, and SQL Server. This improved data accessibility for stakeholders.• Spearheaded Kafka stream ingestion into a Databricks bronze table, reducing latency in real-time data analytics dashboards by 60ms per batch, improving the timeliness of insights and decision-making.• Championed the design and development of a Databricks data validation framework in Python, leading code and design reviews that reduced data defects by 20+ per month.• Redesigned the data warehouse architecture using FSL and SCD Type 1/2 methodologies, reducing query processing time by 40% and data latency by 15ms for 200+ daily users, enhancing overall system efficiency.• Directed the implementation of partitioned tables containing 1.2M+ rows within Azure Data Factory (ADF), boosting query performance by 40% and reducing data retrieval times across the team.• Orchestrated ADO SQL query execution using PostgreSQL metadata mappings in Trino via Airflow, accelerating data retrieval efficiency by 35% across all reporting dashboards.• Containerized and deployed Java-based UDFs to the Trino server on AKS, achieving zero downtime. This enabled complex data transformations, resulting in a 15% improvement in query processing time for analytics dashboards.

Education

• Mariammal Girls Higher Secondary School

  Higher secondary school , Biology, General

• Stateboard

  High School, State Board

• V.S.B. College of Engineering Technical Campus

  Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering

  2014 — 2018