Akanksha Rana

• Azure Ecosystem : Architected end-to-end
pipelines in Azure Data Factory, integrating SQL
Server, REST APIs, and cloud storage, with
optimized activities (Lookup, Foreach, Copy) and
parameterized triggers for efficient, reusable
data flows.
• Cloud Migration Leadership: Directed
on-premises to Azure migrations, converting data
to Parquet for ADLS Gen2 using Azure Databricks,
ensuring secure, centralized access via Unity
Catalog.
• ETL & Data Transformation: Engineered
high-performance ETL pipelines with PySpark and
Spark SQL, implementing joins, aggregations, and
complex logic for large-scale, reliable datasets.
• Performance Optimization: Tuned Azure Data
Factory pipelines, ETL processes, and queries with
partitioning, caching, and indexing, slashing
execution times.
• Azure DevOps Proficiency: Managed Git
repositories, CI/CD pipelines, and Agile workflows
in Azure DevOps, automating builds and
deployments for rapid, reliable delivery.
• SQL Server Expertise: Leveraged SQL Server for
seamless data integration and robust pipeline
support, enhancing ETL and DWH operations. SSIS & DWH Skills: optimized Data Warehousing
structures for and analytics-ready
data. Troubleshooting & Collaboration: Resolved
production issues swiftly, conducted root cause
analysis, and collaborated with cross-functional
teams for scalable solutions. Monitoring & SLAs: Proactively monitored
pipelines and BI systems, ensuring SLA
compliance and driving continuous
improvements with ServiceNow integration. Client-Focused Innovation: Translated technical specs, delivering
solutions ahead ongoing
training in emerging tech.

• DWH Leadership: Key contributor to Data
Warehousing (DWH) team, managing
high-volume telecom data (Airtel, Vodafone,
Idea) for efficient analysis and reporting.
• Client Collaboration: Spearheaded requirements
gathering, aligning ETL and DWH solutions with
client goals to deliver actionable insights.
•
Data Integration Expertise: Extracted and
consolidated data using SQL, SAP BO, Putty, and
Linux, ensuring seamless integration into
centralized systems.
Data Quality Assurance: Implemented shell
script-based purging and cleansing, upholding
integrity across large datasets.
Big Data Optimization: Utilized Hadoop and Hive
queries for storing, analyzing, and reconciling
massive datasets, boosting performance.
• Project Management: Tracked tasks via JIRA,
ensuring timely updates, issue resolution, and
on-schedule delivery.
• Azure Ecosystem : Extensive experience with
Azure Data Factory, Azure Data Bricks, ADLS, and
PySpark, optimizing cloud-based data pipelines
and big data solutions.

• Data Processing: Cleaned and structured
large-scale unstructured data (Walmart, Amazon
web scraping) into high-quality datasets.
Analyzed weekly/off-cycle ads using
geolocation, pricing, and trend data to deliver
actionable insights and boost performance.
• SQL & ETL: Developed optimized SQL queries,
stored procedures, and high-performance SSIS
packages for processing and reporting on
complex datasets with accuracy and efficiency.
• SSAS & Power BI: Built scalable SSAS Tabular
Models integrated with Power BI for advanced
analytics and intuitive dashboards.
• Data Quality & Visualization: Ensured data
accuracy and built compelling Power BI
visualizations by optimizing data models and
relationships.
• Statistical Analysis: Applied statistical methods for
business reporting and strategic decision-making.