Sanan Amir

SANAN AAMIR

EXPERTISE

Data Engineer & AI Specialist

DATE OF BIRTH

30 July 1992

EDUCATION

MS Computer Science | AI/ML

LOCATION

Dallas, TX

EMAIL

info@sananamir.com

PHONE

+1 (262) 888-8559

ABOUT

7+

YEARS OF EXPERIENCE

I am a seasoned full-stack/backend engineer with expertise in machine learning. With a strong background in software development and a passion for solving complex problems, I have honed my skills in designing and implementing scalable, efficient, and robust systems. As a machine learning expert, I am well-versed in a wide range of algorithms, frameworks, and tools, and have experience in applying them to diverse real-world applications. With a keen eye for detail and a commitment to delivering high-quality work, I am always striving to stay on top of the latest developments in my field and to apply my knowledge to create innovative solutions that exceed expectations.

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ETL

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Data Warehousing

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SQL

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Python

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Apache Hadoop

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Apache Spark

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NoSQL Databases

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Data Modeling

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Data Architecture

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AWS

E X P E R I E N C E

BumpUp Solutions

Lead Data Engineer | 2020 – Present
Dallas, TX

  • Leading end-to-end research, development, and implementation of BumpUp Solution enterprise-wide data engineering projects, ensuring alignment with organizational goals.
  • Conducting vendor feasibility research to identify best-fit solutions for data pipeline development, data storage, and processing technologies.
  • Developing and optimizing large-scale ETL processes and data pipelines using technologies such as Apache Kafka, Apache Spark, and Apache Airflow.
  • Designing and implementing data warehousing solutions using cloud-based technologies such as AWS Redshift, Google BigQuery.
  • Ensuring data quality and integrity through the implementation of data validation, cleansing, and transformation techniques.
  • Collaborating with data scientists to develop scalable data processing workflows and to integrate AI/ML models into the data pipeline.
  • Creating and maintaining data documentation, including data dictionaries, data lineage, and data catalog, to facilitate better understanding and usage of data assets across the organization.
  • Proactively monitoring data pipelines and infrastructure, addressing performance bottlenecks, and ensuring high availability and reliability of data engineering solutions.

Take Command Health

Lead Engineer | 2019 – 2020
Dallas, TX

  • Founding Engineer who led the research & development of a pioneering HRA (Health Reimbursement Arrangement) web portal platform.
  • Responsibilities spanned across the whole spectrum: core engineering delivery to providing high touch AI/ML solutions.
  • Reported directly to the CTO and set the quarterly vision & goals for the technology team.
  • Established TCH’s HRA Admin web portal platform as the leading product in the HRA industry (200% user growth in 6 months).
  • Reduced TCH’s manual compliance operations overhead (by 80%) by introducing Optical Character Recognition ML service coupled with entity recognition models within the compliance flows.
  • Envisioned & delivered a user-friendly Reporting & Analytics dashboard to give customers more insights into their monthly reimbursement statements.
  • Led various technical & product strategy discussions to ensure TCH’s long term platform growth.
  • Enabled TCH to establish itself as the dominant HRA product & resultantly raised investment during COVID-19.
  • Utilized various industry leading technologies like Python, React, Redux & AWS cloud & AI/ML services to create a flexible & intuitive product.
  • Led & mentored junior devs to ensure great Team synergy and sharing of knowledge base.
  • Significantly reduced overall production bugs by enforcing strong unit test coverage, PR process & QA testing.

Southwest Airlines Co.

Software Engineer, Enterprise Data & Analytics | 2016 – 2019
Dallas, TX

  • Lead POC engineer for Data for Enterprise initiative to simply data related needs & solutions at Southwest.
  • Performed research on various Big Data tools: Hadoop, Spark, Hive, Tableau, Alteryx etc.
  • Developed robust RESTful APIs for SWA’s new Res System using Spring Boot.
  • Performed feasibility research of porting on-premises apps to AWS.
  • Architected & Developed workarounds to integrate legacy apps with new apps for security compliance using Camel, JMS and other integration tools.
  • Built an in-house Data Quality Checker Web App in React-Redux to assist in data consistency analysis.
  • Led major deployment initiatives and on-call support to ensure smooth operations.

P r o j e c t s

Telecom Data Ingestion Pipeline

Designed and developed a data ingestion pipeline for a telecom provider, enabling real-time data processing and analysis of network performance metrics. Utilized Apache Kafka, Spark Streaming, and AWS services to build a scalable and fault-tolerant solution.

Health Data Warehousing Solution

Implemented a data warehousing solution for a health tech startup, integrating data from multiple sources such as electronic health records, wearables, and mobile apps. Designed the data model and developed ETL workflows using Python and SQL, enabling advanced analytics and insights into patient health trends.

Telecom Network Monitoring Dashboard

Built a web-based dashboard for a telecom provider, providing real-time insights into network performance metrics such as call drops, signal strength, and data usage. Utilized technologies such as Flask, React, and D3.js to create an interactive and responsive user interface.

Health Data Analytics Platform

Developed a cloud-based analytics platform for a health tech startup, enabling advanced analytics and machine learning on large volumes of health data. Utilized AWS services such as Redshift, S3, and SageMaker to build a scalable and cost-effective solution.

Telecom Fraud Detection System

Designed and implemented a fraud detection system for a telecom provider, enabling real-time detection and prevention of fraudulent activities such as SIM swapping and call spoofing. Utilized machine learning algorithms and data visualization techniques to build a predictive model and provide actionable insights to the security team

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