Ahemad Ali Shaik
Irving,TX
Summary
Results-driven Technical Architect with a strong background of Building data pipelines and Cloud Architecture with expertise in Gen AI and MLOps. Skilled in designing and implementing scalable data solutions on Azure and GCP, specializing in Big Data management and cloud migration. Demonstrated success in overseeing end-to-end data projects, driving efficiency, and ensuring optimal performance. Excels at collaborating with cross-functional teams to deliver innovative solutions that meet business objectives.
Overview
13
13
years of professional experience
1
1
Certification
Work History
Technical Architect
Verzion
10.2024 - Current
- Designed and implemented comprehensive data strategies, aligning with business processes and stakeholders needs.
- Developed conceptual, logical, and physical data models using ERWIN, ensuring data consistency and integrity.
- Utilized modern data architecture technologies such as GCP, BigQuery, Azure,Snowflake, and CloudSQL to manage and integrate data.
- Collaborated with stakeholders to define, govern, and maintain data technology architecture, including data platforms, integration, and application development.
- Applied data analytics tools and techniques to drive business insights, and supported the development of data dictionaries and metadata.
- Worked effectively with cross-functional teams, including application development, database development, and stakeholders to deliver data-driven solutions.
- Ensured data quality and integrity throughout its lifecycle, from creation to retirement.
- Demonstrated expertise in DBMS technologies, data integration tools, and stream processing technologies like Kafka and Pulsar.
- Utilized data modeling and analytics expertise to drive business decisions, improve processes, and optimize outcomes.
- Architected robust data pipelines and ETL frameworks for high-velocity, high-volume data, ensuring seamless integration with AI/ML systems and adherence to data governance policies.
- Led cross-functional teams to identify, prototype, and deploy Gen AI solutions for key business challenges, driving a 30% reduction in operational costs and a 40% increase in customer engagement.
- Collaborated with product and engineering teams to design scalable APIs and fine-tuning frameworks, enabling seamless integration of Gen AI into customer-facing applications.
Lead Data Engineer
Verizon
08.2023 - 09.2024
- Headed the design and development of high-performance data platform, leading a team of engineers to achieve scalability and reliability in large-scale data handling.
- Expertize in building data pipelines using Python/Pyspark.
- Developed and deployed AI-driven customer support chatbots using GPT-4 to automate common telecom inquiries (billing, service activation), improving response times and reducing operational costs.
- Implemented LLM-powered natural language processing (NLP) models to automatically categorize and extract insights from unstructured telecom data (e.g., network logs, service tickets), streamlining troubleshooting and network optimization processes
- Utilized GCP services such as Dataflow, Dataproc, and Pub/Sub to ingest, process, and transform large datasets, ensuring high availability and reliability.
- Implemented data warehousing solutions using BigQuery, managing data modeling, ETL/ELT processes, and query optimization for improved data analysis and reporting.
- Utilized GCP's AI Platform and AutoML services to design, train, and deploy machine learning models, integrating them with data pipelines and applications.
- Implemented data encryption, access controls, and auditing using GCP services such as IAM, KMS, and Data Loss Prevention, ensuring compliance with regulatory requirements
- Highly motivated Data Engineer with expertise in designing, developing, and deploying scalable data pipelines using Python, PySpark, and SQL.
- Proficient in data processing, transformation, and analysis using Big Data technologies.
- Ingest petabytes of data from diverse sources, including streaming and batch
- Ensure the application's scalability, utilizing serverless architecture, and implementing automation to streamline operations.
- Focus on optimizing the data loading process and achieving sub-second query performance for end-users, while prioritizing cost efficiency.
- Implement cost optimization techniques and at the same time make sure that Quality and SLAs are not breached
- Successfully managed a team of delivery drivers, ensuring timely and accurate delivery of products to customers
- Implemented new delivery routes and strategies to optimize efficiency and reduce delivery times
- Monitored and tracked delivery performance metrics, identifying areas for improvement and implementing corrective actions
- Collaborated with cross-functional teams to ensure smooth coordination and execution of delivery operations
- Oversaw the implementation of Bigtable as the primary data storage solution, providing technical guidance on schema design and data modeling to ensure optimal performance and availability.
- Led the adoption of microservices-based architectures and built high performance RESTFUL APIs for critical applications, leveraging Kafka to enable seamless communication and data exchange between services, and ensuring successful integration with existing systems.
- Developed and enforced advanced data governance and validation strategies across the team, ensuring efficient collaboration and code management.
- Championed the use of Swagger for comprehensive API documentation, leading by example to ensure clear and concise communication of API endpoints and data models.
- Led the development and deployment of complete application from data collection to API and Kubernetes resources monitoring dashboards using ELK , providing real-time insights into API performance and usage metrics, and driving data-driven decision making.
Technical Lead
Verizon
10.2022 - 07.2023
- Lead the migration project mentioned above, which involves transferring a datalake exceeding 100 petabytes in size from on-premises to the Google Cloud platform.
- Developed a real-time data analytics platform using PySpark, Apache Kafka, and BigQuery
- Built a data warehousing solution using BigQuery, Python, and SQL
- Created data visualizations using Tableau and Matplotlib for business stakeholders
- Define migration goals, such as scalability, performance, and cost optimization.
- Develop a migration strategy that accounts for the scale and complexity of the data lake.
- Establish cost monitoring and governance practices to track cloud spending and identify opportunities for optimization.
- Enhance resource utilization and boost performance by optimizing storage and database systems.
- Address complex migration issues and mentor the team to complete the migration within the agreed-upon timeframe.
- Successfully implemented cloud migration strategy resulting in an annual cost reduction of 30%.
Technical Architect
Verizon
04.2022 - 09.2022
- Spearheaded migration of petabyte-scale data warehouses and batch pipelines to GCP, utilizing Dataflow, Dataproc, and BigQuery, achieving 300% performance improvement and 40% cost reduction
- Designed and implemented cloud-native data lakes, warehouses, and pipelines leveraging GCP services (Cloud Storage, Pub/Sub, BigQuery), ensuring scalability, reliability, and data governance.
- Assess the existing Dataproc-based jobs and their dependencies to understand the workload requirements, data sources, and processing logic.
- Identify the key components, data pipelines, and transformations involved in the workload to be migrated.
- Identify any potential challenges or limitations in migrating from Dataproc to BigQuery through POCs, such as differences in data processing capabilities or query optimization techniques.
- Design and implement data pipelines using Apache Airflow to orchestrate and schedule the migration tasks from Oozie to Airflow, processes, and data transfers between Hive and BigQuery.
- Revise PySpark-based data processing scripts to utilize BigQuery's inherent functionalities for data analysis and transformation wherever feasible, and transition Spark library-dependent workloads to serverless environments.
Lead Cloud Engineer
Windstream
10.2020 - 02.2022
- Designed and developed high-performance RESTful APIs using Spring Boot, handling large volumes of data and achieving scalability and reliability.
- Successfully implemented data storage solutions using Snowflake, leveraging its flexible schema and high availability features to support massive data growth.
- Built and deployed microservices-based architectures, utilizing Spring Kafka for seamless communication and data exchange between services.
- Implement DevOps practices and set up CI/CD pipelines to automate deployment and management of Azure resources and applications.
- Utilize Azure DevOps services to streamline development workflows, improve collaboration, and ensure consistency and reliability in the cloud environment.
Sr Data and MLOps engineer
Windstream
02.2019 - 09.2020
- Develop data pipelines to ingest streaming device performance data, ensuring continuous flow and reliability. Cleanse and preprocess the data to handle missing values, outliers, and inconsistencies, ensuring high-quality input for model training.
- Build machine learning models to predict network fault performance using the cleaned data. Utilize MLops (Machine Learning Operations) practices to streamline model development, versioning, and deployment, ensuring reproducibility and scalability.
- Deploy the trained models to predict network faults and identify devices at risk of failure. Leverage real-time monitoring and alerting systems to promptly notify stakeholders of potential issues, enabling proactive maintenance and minimizing downtime.
- Conduct impact analysis to determine the potential ripple effects of device failures on other network components. Utilize the predictive models to forecast the devices likely to be impacted by faults, enabling preemptive actions to mitigate disruptions and maintain network stability.
- Develop APIs and reports to share the predictions and alerts to stakeholders and network team.
Data Engineer and Graph Database Developer
Windstream
04.2018 - 01.2019
- Design and implement Directed Acyclic Graphs (DAGs) to extract, transform, and load (ETL) data from Oracle sources into the data lake. Ensure data availability and quality for downstream consumers through robust data pipeline architecture.
- Develop a graph-based application for network devices connections inventory and planning. Utilize graph database technology to model network relationships and optimize network infrastructure planning processes.
- Successfully implement the graph application, resulting in a 45% increase in efficiency for network device connections inventory and planning tasks. This improvement streamlines operations and enhances productivity across the network management team.
- Continuously monitor and optimize the ETL DAGs and platform to ensure optimal performance, scalability, and reliability.
- Implement feedback mechanisms to gather user input and incorporate enhancements based on evolving requirements.
BigData Admin and DevOps engineer
Windstream
07.2015 - 03.2018
- installation and configuration of Cloudera clusters, ensuring optimal performance, scalability, and reliability for the data lake infrastructure.
- Architect and build the data lake environment, implementing best practices for data storage, organization, and access control. Continuously monitor and maintain the data lake to ensure data availability and integrity.
- Implement security upgrades and patches for Cloudera clusters, proactively.
- addressing vulnerabilities and ensuring compliance with data security standards and regulations.
- Collaborate with the team to design and implement data ingestion pipelines for streaming and batch data sources, enabling seamless data flow into the data lake.
- Containerize data processing applications and services using Kubernetes and Docker, facilitating deployment, scalability, and management of containerized workloads within the data lake environment.
Data Migration Specialist
Windstream
05.2014 - 06.2015
- conversion effort to migrate the Billing application to another application database.
- Understand the structure and data model of both applications to identify similarities and differences and Map the data elements from the source application's DB2 database to the target application's database schema.
- Extract data from the source DB2 database and perform the data transformations or conversions needed to ensure compatibility of target system.
- Load the extracted and transformed data into the target application's database,following the target application's data-loading procedures and best practices.
- Verify the accuracy and completeness of the data after loading to ensure successful migration, take care of fallouts from migration and run them through additional script.
Application Programmer
Centurylink
07.2013 - 04.2014
- Develop and enhance late payment penalty functionality within the existing system, ensuring accurate calculation and application of penalties for overdue payments.
- Implement changes to user screens to accommodate the new late payment penalty features, providing clear and intuitive interfaces for users to manage penalties. Make necessary modifications to the backend database schema to support the updated functionality and ensure data integrity.
- Conduct thorough testing of the developed features and enhancements to ensure reliability, accuracy, and compliance with business requirements.
- Deploy the changes to the production environment in a controlled manner, minimizing disruption to users and operations.
Application Developer
Centurylink
01.2012 - 06.2013
- Provide ongoing support and enhancements for the order management application and continuously optimize application performance and functionality based on user feedback and evolving business requirements.
- Automate manual tasks using macros to streamline processes and improve efficiency.
- Develop and implement reports tailored to the needs of business users to facilitate informed decision-making and collaborate with stakeholders to identify opportunities for further automation and enhancement to drive operational excellence.
Education
Engineering - Computer science
NBKRIST
Vidhyanagar,IndiaSkills
- Python
- Web/rest APIs
- Hadoop/Bigdata
- Linux
- Mongo DB
- Kubernetes/Docker
- BigQuery/Cassandra
- Spark
- Snowflake
- MLOps
- Gen AI
- NiFi
- Airflow/Oozie
- GCP/Azure
- CI/CD and Automation
- Kafka/Pulsar
- Prometheus/Grafana/ELK
- Microservices
- Clickhouse
- Apache Druid
- Mainframe/DB2
- Cloudera
- Gen AI/ LLMs/Agent AI
- GraphQL
MLflow/AWS sagemaker
Certification
Google cloud professional architect Google Cloud January 2024
Google cloud professional data engineer Google Cloud June 2022
Microsoft Azure Devops expert Microsoft August 2020
Microsoft Azure administratror Microsoft July 2019
Custom Section
- Delivery champion of the year for 2019 in Prodapt Annual awards.
- Technical Champion of the year for 2021 in Prodapt Annual awards.
- Star of the Quarter for Q4 2023 in Prodapt Quarterly awards.
Timeline
Technical Architect
Verzion
10.2024 - Current
Lead Data Engineer
Verizon
08.2023 - 09.2024
Technical Lead
Verizon
10.2022 - 07.2023
Technical Architect
Verizon
04.2022 - 09.2022
Lead Cloud Engineer
Windstream
10.2020 - 02.2022
Sr Data and MLOps engineer
Windstream
02.2019 - 09.2020
Data Engineer and Graph Database Developer
Windstream
04.2018 - 01.2019
BigData Admin and DevOps engineer
Windstream
07.2015 - 03.2018
Data Migration Specialist
Windstream
05.2014 - 06.2015
Application Programmer
Centurylink
07.2013 - 04.2014
Application Developer
Centurylink
01.2012 - 06.2013
Google cloud professional architect Google Cloud January 2024
Google cloud professional data engineer Google Cloud June 2022
Microsoft Azure Devops expert Microsoft August 2020
Microsoft Azure administratror Microsoft July 2019
Engineering - Computer science
NBKRIST
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