Skills
PythonAbout me
I am an experienced and highly motivated solution expert, dedicated to delivering robust data engineering solutions. With a strong background in designing, developing, and maintaining data architectures, I specialize in implementing data solutions using Databricks, Delta Lake, Azure Data Factory, SQL, Spark, PySpark, ADLS Gen2, and Azure Synapse.
I have successfully led SAS to PySpark migration projects, demonstrating my ability to adapt and innovate with new technologies. My expertise extends to CI/CD, automation, Docker, Power BI, Git, GitHub, Azure Functions, Hive, and Hadoop, allowing me to create efficient, scalable, and automated data workflows.
One of my key strengths is optimizing solutions to reduce costs. I have a proven track record in optimizing data pipelines and Sparkapplications, resulting in significant cost savings for organizations. By streamlining processes and leveraging best practices, I ensure that data solutions are not only effective but also economical.
Expertise
Data Flow
Designed and implemented robust data pipelines to ensure seamless data flow across various stages within a Cloudera Hadoop ecosystem. By orchestrating seamless data migration, We successfully revamped data pipelines by transitioning from SAS to PySpark, ensuring enhanced efficiency and scalability.
Optimization
Experienced in data pipeline optimization, focusing on enhancing efficiency and performance. Optimized data pipelines by optimizing storage solutions to improve performance and scalability, and meticulously monitoring and fine-tuning Spark to efficiently handle large data volumes.
Data Analytics
In addition to my experience in delivering data for visualization seamlessly and maintaining data consistency, I possess strong knowledge on data preprocessing, visualization libraries matplotlib, plotly and Power BI certified. It enhances my ability to create insightful visualizations for effective data communication.
Design Patterns
As a data engineer, I consistently applied OOPS concepts while writing Python Spark code for data engineering tasks. By utilizing OOP principles, I ensured that the codebase was modular, maintainable, and scalable, leading to efficient data processing pipelines.
ETL Design
With data engineering, I posses an experiencem on Extract, Transform, Load (ETL) processes, including the migration of SAS applications to Hadoop using PySpark. Additionally, I've developed ad hoc PySpark scripts to address specific data processing requirements, ensuring seamless integration and efficient data processing within the Cloudera and Azure ecosystem.
Banking / IOT
Experienced in working on both banking and Internet of Things (IoT) projects. In particular, my expertise includes processing IoT sensor data efficiently. Through my knowledge of IoT systems, I've developed strategies for collecting, processing, and analyzing sensor data to extract valuable insights for various applications.
WORKS COMPLETED
+
YEARS OF EXPERIENCE
~
TOTAL CONNECTIONS
CERTIFICATIONS
Blog
Big Data
Let's Talk about Big Data
Big data refers to large and complex data sets that are beyond the processing capabilities of traditional data management tools. It's characterized by the three Vs: volume, velocity, and variety.
- Volume : Big data involves massive amounts of data, often ranging from terabytes to petabytes or even exabytes. This includes data from various sources such as social media, sensors, transactions, and more.
- Velocity : Data is generated at an unprecedented speed, sometimes in real-time or near real-time. For example, social media platforms generate millions of tweets, posts, and interactions every second.
- Variety : Big data comes in various formats and types, including structured, semi-structured, and unstructured data. Structured data can be easily organized into tables, like data in databases, while unstructured data, such as text, images, and videos, lacks a predefined structure.
Data Quality
Get some idea on Data Quality
Data quality is essential for any organization to derive accurate insights and make informed decisions. Here are some key aspects of data quality:
- Accuracy : Data should accurately reflect the reality it represents. Errors, inconsistencies, or outdated information can lead to misleading conclusions.
- Completeness : Data should be complete, containing all necessary information for its intended purpose. Missing or incomplete data can introduce biases and skew analyses.
- Consistency : Data should be consistent across different sources, systems, and time periods. Inconsistencies can arise from duplicate records, variations in data formats, or conflicting information.
- Timeliness : Data should be up-to-date and relevant for the analysis or decision-making process. Outdated data may no longer reflect the current state of affairs and can lead to inaccurate conclusions.
- Relevance : Data should be relevant to the analysis or business objectives at hand. Irrelevant or extraneous data can clutter datasets and obscure meaningful insights.
Travel
Let's drive into Travelling and Fun
I embarked on my journey from Northern part of India, where I explored the majestic Himalayas, traversed through the desert landscapes of Rajasthan, and discovered the serene beaches from south india along the coastline. This diverse and captivating region ignited my passion for travel and inspired me to explore more destinations around the world.
The Himalayan region in northern India is renowned for its breathtaking landscapes, towering peaks, and rich cultural heritage. Whether trekking in the Garhwal or Kumaon region of Uttarakhand, exploring the hill stations of Himachal Pradesh like Shimla and Manali, or visiting spiritual centers like Rishikesh and Haridwar, the Himalayas offer a blend of adventure, spirituality, and natural beauty.
Embarking on a thrilling bike trip to Manali, I was captivated by the enchanting beauty of Old Manali and the awe-inspiring vistas along the iconic Rohtang Pass. The journey through winding mountain roads offered breathtaking panoramas of snow-capped peaks, and lush valleys, leaving an indelible mark on my soul and igniting a sense of wanderlust that continues to drive my adventures.