Srikanth Pasagodugula
Data Engineer • Vijayawada, Andhra Pradesh, India • s**************@gmail.com • 939****945 • linkedin.com/•••••
Professional Summary
Data Engineer with 2+ years of hands-on experience designing, building, and optimizing scalable ETL/ELT pipelines and data platforms on Microsoft Azure. Experienced with Azure Data Factory, Databricks, PySpark, Delta Lake and Synapse to enable reliable analytics and reporting. Strong focus on data quality, performance tuning, and cross-functional delivery of analytics solutions. Seeking a data engineering role where I can apply cloud data platform expertise to deliver robust, production-grade data solutions and drive measurable business outcomes.
Technical Skills
Programming Languages: Python
Frameworks and Libraries: Apache Spark,PySpark,Spark SQL
Databases: SQL,SQL Server,Snowflake
Data and Analytics: Azure Databricks,Azure Data Factory,Azure Synapse Analytics,Microsoft Fabric,Data Modeling,Star Schema,Snowflake Schema,Power BI,ETL Processes,ELT Processes,Data Pipelines,Data Quality,Data Integration
Tools and Methodologies: Git,GitHub
Storage & Warehousing: Azure Data Lake ADLS,Delta Lake,Azure SQL
Work Experience
JCS HUB
Bengaluru, India
Data Engineer
Feb 2024 – Present
Tech Stack: Azure Data Factory, Azure Databricks, PySpark, Spark SQL, Azure Data Lake ADLS, Azure Synapse Analytics, Azure SQL, Delta Lake, Power BI, Git, GitHub, Azure Key Vault, Unity Catalog
- Designed and implemented scalable ETL/ELT pipelines using Azure Data Factory, Azure Databricks, PySpark and SQL to ingest and transform large-scale enterprise data for analytics consumers, improving delivery consistency and reducing manual effort.
- Built and optimized ingestion workflows across Azure Data Lake (ADLS), Azure SQL and Azure Synapse, streamlining data flow and improving pipeline throughput and stability for reporting and analytics teams.
- Implemented distributed PySpark processing and Spark SQL optimizations (partitioning, caching, broadcast joins) to reduce job runtimes and increase reliability of nightly batch processing.
- Integrated Delta Lake to enable ACID transactions and incremental loading strategies, supporting reliable CDC-style loads and simplified time-travel for troubleshooting and analytics accuracy.
- Established data quality checks, monitoring and alerting within ADF/Databricks notebooks and pipeline triggers; collaborated with data owners and analysts to resolve upstream data issues prior to production consumption.
- Managed source control and deployment workflows using Git and GitHub; documented data models, lineage and operational runbooks to accelerate handoffs and reduce incident resolution time.
Projects
Hyndalco Pipeline Control Tower
Tools Used: Azure Data Factory, Azure Databricks, PySpark, Power BI, Azure Synapse Analytics
- Developed scalable data pipelines and distributed processing workflows to handle high-volume enterprise telemetry and operational data, improving reliability of downstream analytics.
- Tuned transformation logic and workload distribution across Databricks clusters to increase pipeline stability and reduce processing bottlenecks for production reports.
Cloud Shop Optimization
Tools Used: Azure Data Factory, Azure Databricks, PySpark, Azure Synapse Analytics, Delta Lake, Power BI
- Built ETL workflows to process retail and customer analytics data in cloud environments, enabling timely KPI reporting for merchandising and marketing stakeholders.
- Implemented Delta Lake incremental loading and Synapse warehousing patterns to support efficient data refreshes and business-facing Power BI dashboards.
Education
SRK Institute of Information Technology
Bachelor of Technology - BTech, CSD • Vijayawada, Andhra Pradesh, India • 2022 – 2025
Certifications
Microsoft Azure Administrator (AZ-104) — Mind Luster
Microsoft Azure Fundamentals (AZ-900) — Mind Luster
Data Engineering — EduSkills
Python Programming — Besant Technologies
SQL and Relational Databases 101 — IBM Developer Skills Network
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