Azure Data Engineer - Azure Medallion & Spark

ABHILASH RANABOTHU

Toronto, ON • 226-***-**** • ******************@*****.*** • linkedin.com/in/abhilash-ranabothu PROFESSIONAL SUMMARY

Azure Data Engineer with 3 years of enterprise experience specializing in cloud-native ETL and ELT pipelines, distributed processing, and production-grade architectures. Proven expertise across Canadian Tire retail platforms architecting Medallion data lakehouses, implementing advanced Spark optimization patterns such as salting and broadcasting, and automating multi-environment CI and CD release cycles. Track record of delivering scalable data infrastructure that significantly minimizes query latencies and cloud consumption costs.

CORE TECHNICAL SKILLS

Cloud & Orchestration: Azure Data Factory (ADF), Databricks, Azure Synapse Analytics, Logic Apps, Event-Driven Triggers Data Processing: Apache Spark, PySpark, Spark SQL, Delta Lake Lakehouse architecture, T-SQL Storage & Databases: ADLS Gen2, Azure SQL DB, Azure Cosmos DB, PostgreSQL, SQL Server, Snowflake Schema Languages & DevOps: Python (Advanced), SQL (Expert), Azure DevOps, CI and CD Pipelines, Terraform (IaC), Git, GitHub Security & Quality: Azure Key Vault, RBAC, Data Masking, Schema Drift Detection, Anomaly Detection Frameworks PROFESSIONAL EXPERIENCE

AZURE DATA ENGINEER • Canadian Tire Aug 2023 – Present

• Spark Optimization & Performance: Mitigated Spark data skew during massive retail fact table joins by implementing salted keys and broadcasting dimension tables; reduced job execution times by 40 percent and stabilized critical SLAs.

• Enterprise Data Platform Migration: Led end-to-end migration of 14 plus legacy on-premises SQL Server databases to an Azure Medallion architecture (Bronze/Silver/Gold); slashed data refresh latency from 5 hours to less than 25 minutes and reduced infrastructure footprint by 28 percent.

• Cloud FinOps & Cost Engineering: Programmed auto-pause and auto-scale policies and compute-pool workloads within Azure Synapse Analytics and Databricks clusters, dropping monthly cloud consumption spend by 20 percent (saving over 2200 dollars per month).

• Data Pipeline Robustness: Designed 22 plus fully dynamic, parameterized ingestion pipelines via Azure Data Factory (ADF); incorporated custom control tables and checkpointing logic that increased scheduled pipeline success rates from 89 percent to 98.5 percent.

• Production-Grade Engineering Frameworks: Built an automated Python-based data quality framework to detect duplicate SKUs or UPCs and schema drift across e-commerce and POS streams, minimizing out-of-stock reporting anomalies by 22 percent.

• API Resiliency Engineering: Overcame third-party e-commerce API rate-limiting and throttling failures by implementing an exponential backoff retry and batching architecture, preserving pipeline continuity during high-volume sales spikes.

• DevOps & Enterprise Automation: Standardized multi-banner regional deployments by externalizing pipeline parameters using ARM Templates and Azure Key Vault, decreasing post-release environment defects by 30 percent via automated testing gates.

• BI Query Acceleration: Optimized Power BI semantic models and Synapse hash or round-robin distribution keys, accelerating end-to-end dashboard load performance by 35 percent for executive stakeholder reporting layers. EDUCATION

Bachelor of Technology (B.Tech.) — Mechanical Engineering JNTU Hyderabad 2016 – 2020

Contact this candidate