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Murali - AWS Data Engineer

[email protected]

Location: Dallas, Texas, USA

Relocation: Yes

Visa: GC

Muralidhar R Sr. AWSData Engineer (312) 788-8782 PROFESSIONAL SUMMARY: Currently seeking Senior/Lead Data Engineer roles leveraging 11+ years of expertise across Azure & AWS cloud platforms, enterprise data lakes, and AI/ML pipelines. Proven track record as an Azure Migration Engineer, leading end-to-end migrations of on-premises workloads to Azure using ADF, Databricks, Synapse Analytics, ADLS, Azure SQL Database/Warehouse, Service Bus, Key Vault, AAS, Blob Storage, Azure Search, App Service, Azure Kubernetes Service (AKS), Apache Kafka, and Snowflake. Designed and implemented hybrid connectivity between Azure and on-premises using Virtual Networks, VPN, and ExpressRoute, ensuring secure, scalable integrations. Skilled in AWS services including S3, EC2, VPC, EMR, Redshift, Lambda, Glue, RDS, DynamoDB, Athena, Step Functions, SNS, SQS, with additional experience in Kinesis, IAM, and CloudWatch, delivering big data pipelines, real-time streaming solutions, and enterprise-scale platforms. Strong background in data engineering with Hadoop & Spark ecosystems (HDFS, MapReduce, Hive, Sqoop, Oozie, Spark SQL, Spark Streaming, PySpark, RDDs, Scala/Python), optimizing distributed data processing and performance. Designed and deployed ML pipelines on Azure Databricks leveraging PySpark and MLflow for preprocessing, training, and model tracking; implemented MLOps practices with Azure ML, Azure DevOps, Jenkins, and XL Release. Built predictive and deep learning models using Scikit-learn, TensorFlow, and PyTorch, integrated into ADF pipelines for automated training, scoring, and monitoring dashboards. Proficient in Python (Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn) for analysis, visualization, and ML workflows; experienced in building REST APIs and deploying models on Databricks. Strong expertise in SQL & T-SQL, Snowflake, Oracle, SQL Server, MongoDB, Cassandra, and MySQL, with advanced knowledge of dimensional modeling (Star & Snowflake schemas, Fact/Dimension tables). Delivered enterprise-level monitoring and alerting solutions with Elastic Search, ServiceNow, Datadog, and PagerDuty, improving observability, reliability, and incident response. Experienced in BI reporting and analytics with Power BI, Tableau, and POSIT Connect, enabling insights and decision-making for business stakeholders. Implemented Azure Purview for enterprise-wide data governance, metadata cataloging, and lineage tracking to support compliance and regulatory requirements. Built real-time ingestion and processing pipelines using Azure Stream Analytics integrated with Event Hubs and Kafka, enabling sub-second insights and automated alerts. Optimized big data workloads by leveraging Azure HDInsight (Hive, Pig, Sqoop) before modernizing into ADLS Gen2 and Synapse, improving scalability and performance. Provided team leadership by mentoring 5+ junior engineers, coordinating sprint planning, and managing stakeholder communication across compliance, governance, and product teams, ensuring timely delivery of Azure and AWS data solutions. Certifications: Azure Databricks Associate Developer for Apache Spark 3.0, Azure AI Fundamentals (AI-900), DP-203 (Azure Data Engineer), AWS Certified Data Analytics Specialty. Keywords: artificial intelligence machine learning business intelligence sthree rlang