Garry Singh

Accomplished Senior Software Engineer with over 13 years of experience, specializing in the dynamic aspects of Software Engineering including Data Engineering, Machine Learning and Data Analytics. 

• Proven expertise of 8+ years in Python for high volume data integration flows, data analysis & machine learning. 
• Deep rooted knowledge & hands on experience of over 7+ years in Core Java and 5+ years in Scala development. 
• Skilled and Certified in Multi-Cloud Solutions, adept at utilizing a stack of cloud technologies across Microsoft Azure (7+ years), AWS (4+ years), and Google Cloud (3+ years).
• Experienced in working on enterprise scale ETL, Data Orchestration & Data Pipelining projects with expertise in comprehensive data ingestions/integrations, data governance, real-time and batching strategies. 
• Successfully delivered fast-paced projects across domains including Banking (securities, capital markets), Retail (operations), Healthcare (benefits delivery), FinTech (market risk) and Government (regulatory reporting).

Company: IBM / Ministry of Employment and Social Development (ESDC), London UK
Position: Principal Software Engineer (Aug 2022 – Apr 2024) 
Project: Benefits Delivery Modernization and Old Age Security (BDM/OAS) 

• Spearheaded the development and deployment of machine learning models using Python TensorFlow on Azure Kubernetes clusters, aimed to drive an artificial intelligence program for real-time transaction anomaly detection. 
• Developed guaranteed delivery File to API pattern microservices using Java Springboot, Azure ADF, Azure APIM (TLS encryption and OAuth 2.0) & Apache Kafka, facilitating real-time data flow of millions benefit payments. 
• Programmed and reported data integrity and data governance indicators using PySpark, Pandas, Matplotlib & TensorFlow, extracting actionable business insights from intricate healthcare and financial datasets. 
• Engineered sophisticated data integration and analytics workflows by orchestrating Apache NiFi pipelines, seamlessly integrating Azure Blob Storage, and employing Spark Scala within Azure Databricks. 
• Deployed the ELK stack (Elasticsearch, Logstash, Kibana) to establish a comprehensive monitoring solution, guaranteeing peak system performance and enabling swift issue resolution. 
• Implemented data profiling and quality checks using Python (YData-profiling lib) resulting in a reduction of data related outliers and errors by 30%. 

Company: Northern Trust, London, UK 
Position: Lead Senior Software Engineer (Apr 2021 – Aug 2022) 
Project: GRM Enterprise Market Risk 

• Developed functional data flows using Scala and Spark Structured Streaming on AWS infrastructure, processing on an average 10 million position & adjustments data metrics, significantly enhancing accuracy in risk reporting. 
• Optimized SQL Server and Cassandra database scripts, to efficiently handle multi-structured data, focusing on accelerated data retrieval and reduced latency in high-frequency trading environments. 
• Engineered, deployed, and maintained high-performance APIs on the AWS API Gateway, defined with Swagger OpenAPI specifications, exposing intricately processed and enriched treasury data for ad hoc consumption. 
• Developed a robust risk calculation engine, incorporating Java (SpringBatch & Apache Commons Math) and Python (SQLAlchemy, Pandas & NumPy) on AWS EC2 for the Liquidity Risk Reporting to regulatory authorities. 
• Engineered robust solutions leveraging Delta Lake on AWS S3, Lambda, and Glue to streamline data processing workflows, optimizing efficiency, and reducing processing times using storage formats like ORC and Parquet. 
• Engineered functional data flows using Scala and Spark Structured Streaming on AWS infrastructure, precisely processing voluminous position and adjustments data, ensuring accuracy in reporting and analytics. 

Company: TD Bank Toronto, ON 
Position: Senior Solutions Engineer (Mar 2020 – Apr 2021) 
Project: Convertible Trading Platform (CTP) - Capital Market 

• Successfully developed complex business rule processing engine modules using Scala (Play, Akka framework) with Druid & migrated away from Drools-based Java applications, significantly reducing infrastructure overhead. 
• Instituted robust business validation and data integrity processes across multiple Java apps for processing data from consumer Confluent Kafka topics & Spark SQL for dynamic in-memory data validations, & lookups on AWS. 
• Developed Python scripts for data conversion and transformation utilizing data conversion libraries (Pandas, NumPy, Json, CSV, and XML) to perform adhoc data conversion and seamless integrating with AWS Data Lake. 
• Orchestrated a seamless integration of real-time streaming and migration of messaging middleware from Solace systems to Confluent Kafka leveraging Kafka connectors for efficiently processing 5 million transactions daily. 
• Engineered high-throughput and resilient streaming pipelines using Java 11 on AWS Lambda to enable real-time synchronization, transformation, and integration of extensive, multifaceted trading data. 

Company: Albertsons Vancouver, BC 
Position: Senior Data Engineer/Lead Kafka Designer (Jan 2019 – Mar 2020) 
Project: Enterprise Data Integration Services 

• Programmed robust business validation and data integrity processes across multiple Java Spring microservices for processing data from consumer topics, leveraging Confluent Kafka and Spark SQL for in-memory processing. 
• Developed comprehensive streaming & transformations flows by integrating Streamsets pipelines with KStreams, KTables, and KSQL for real-time data processing to Mongo DB across various retail channels on Azure Cloud. 
• Engineered high-throughput and resilient streaming pipelines on Azure ADF to enable real-time synchronization, transformation, and integration of extensive, multifaceted retail data sourced from Blob Storage and Kafka. 
• Supported and executed sophisticated deployment strategies utilizing Azure DevOps and ARM template services leveraging containerized architectures orchestrated via Kubernetes, incorporating secure encryption protocols. 
• Transformed complex hierarchical and nested XML data structures through data orchestration using Streamsets in integration with Python leveraging xmltodict and fastavro libraries for publishing schema-adhered Avro data. 

Company: Royal Bank of Canada Toronto, ON 
Position: Software Engineer (Sep 2014 – Jan 2019) 
Project: CTHUB team of Corporate Treasury 

• Developed, enhanced, and maintained sophisticated enterprise Java applications within the Struts framework to deliver precise reports while harnessing the multithreaded executors & parallel processing capabilities of Spark. 
• Designed and developed DataStage jobs and routines for sequential and parallel flows, executed through workflow automation for ingesting and transforming file feeds from upstream sources with dissimilar formats. 
• Engineered, deployed, and maintained high-performance APIs meticulously defined with Swagger OpenAPI specifications on the AWS API Gateway exposing intricately processed and enriched trading data. 
• Implemented solutions for ingesting data from various sources and processing the Data-at-Rest utilizing Big Data technologies such as Hadoop, MapReduce Frameworks, MongoDB, Hive, Oozie, Flume, Sqoop and Talend. 
• Solutioned optimized data storage utilizing highly compressed and partitioned HDFS Parquet data stores on Google Cloud compute engine, utilizing Cloud SQL & BigQuery for robust, large-scale data querying and analytics

Masters in Software Engineering (AI & ML), Oxford University, (Part-Time), Oxford, UK 
Bachelors in Software Development & Network Engineering, Sheridan College, Toronto, Canada
Bachelors in Business Administration, Vinayaka Missions Sikkim University, Sikkim, India
Specialization Certification in Mathematics for Machine Learning & Data Science, DeepLearning AI 
Specialization Certification in Machine Learning, Stanford University 
Certified Azure AI Engineer Associate, Microsoft 
Certified Associate in Project Management, Project Management Institute