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Click here or scroll down to respond to this candidate Ahmed Shahid
EMAIL AVAILABLE PHONE NUMBER AVAILABLE New York City, NY Street Address
SUMMARY
As a Senior Data Engineer with substantial expertise in Big Data technologies such as Hadoop, Spark, and
Apache Flink, I have significantly advanced data processes within the financial and healthcare sectors. My
tenure includes impactful roles at LYFE Marketing, where I specialized in managing extensive healthcare
datasets, emphasizing compliance and performance enhancements. I possess deep proficiency in Python,
Scala, and Java, and am adept at leveraging cloud platforms like AWS, Azure, and Google Cloud to develop
scalable and secure data infrastructures.
I excel at implementing real-time data processing systems and upholding strict data security and privacy
standards, which are essential for thorough data governance. My expertise also spans creating serverless
architectures and integrating sophisticated analytics solutions, driving innovation and strategic
advancements. I am actively looking for opportunities in organizations that prioritize dynamic data
strategies and effective leadership in data engineering.
PROFESSIONAL EXPERIENCE TECHNICAL SKILLS
Stripe Jan 2018 - Jun 2024 Data Engineering:
Senior Data Engineer Data Modeling, Data
Warehousing, and ETL Processes
At Stripe, I played a key role in upgrading our data handling capabilities,
Developing Data Pipelines using
which was crucial for processing millions of financial transactions daily. My
Big Data Technologies like
work involved:
Hadoop and Spark
Building a real-time data processing platform using Kafka and Apache
Real-time Data Processing with
Flink, which not only sped up transactions but also made our decision-
Apache Kafka and Apache Flink
making processes sharper and more efficient.
Data Streaming and Distributed
Developing scalable data architectures that supported both our day-to-
Systems
day operations and analytical needs. I used Hadoop and Spark
API Development
extensively to manage the huge volumes of data we dealt with, which
Scalability and Performance
also helped us get better at detecting fraud and assessing risks.
Tuning
Enhancing our data governance practices to meet international
Metadata Management, Data
standards like GDPR and CCPA. This meant putting in place stronger
Cataloging, and Lineage
data classification, encryption, and access controls, making sure our
Cloud Solutions:
customers' financial information was always protected.
Cloud Data Solutions across
Managing big financial datasets, where I ensured that everything from
AWS, Azure, and Google Cloud
credit data to transaction records was handled flawlessly. I worked with
Implementing Serverless
PostgreSQL and NoSQL databases like Cassandra to maintain integrity
Architectures
and responsiveness of our databases.
Database Management:
Streamlining data streaming and storage solutions, setting up Kafka for
Database Management Systems:
efficient real-time data streaming and using AWS S3 for our data lakes,
SQL and NoSQL
which significantly improved how we accessed and analyzed data.
Data Governance, Quality
I was constantly on the lookout for ways to enhance our data security and
Management, and Integration
privacy measures, implementing rigorous checks, regular audits, and
Data Security and Privacy
advanced security protocols to keep our data safe. My approach has always
Master Data Management (MDM)
been about making our data processes not just faster but also smarter and
Data Lake Architecture
safer.
LYFE Marketing Jun 2012 - Dec 2017
Data Operations Engineer Data Analytics:
Business Intelligence Tools:
At LYFE Marketing, I significantly enhanced our healthcare data management Tableau and Power BI
systems with a focus on integrating and automating data processes. My work Data Visualization, Data
involved: Wrangling, and Feature
Streamlining healthcare data systems by merging multiple sources into a Engineering
unified repository, ensuring consistent and high-quality data for detailed Programming Languages:
analytics and reporting. Python, Scala, Java and SQL
Spearheading the transition to cloud-based solutions, using AWS and DevOps:
Google Cloud to boost our system s scalability and improve disaster MLOps, CI/CD Pipelines, Version
recovery methods. Control with Git
Innovating with serverless architectures, which included implementing AWS Containerization and
Lambda and API Gateway for efficient, server-free data processing, cutting Orchestration using Jenkins,
down costs and management overhead. Docker and Kubernetes
Developing robust data architectures and ETL pipelines to manage and Advanced Analytics:
process large volumes of medical image data, enhancing the system's Integrating AI and Machine
performance and data quality. Learning in Data Pipelines
Upgrading our data warehousing with AWS Redshift, optimizing storage and Leadership and Management:
access to support complex data analysis. Compliance with Data
Automating continuous data integration to ensure updated and seamless Regulations
data flow, reducing manual efforts and improving system reliability. Effective Leadership and Team
Maintaining high data integrity through strict validation and cleansing, Management
supporting accurate and dependable analytics for decision-making. Project Management, Strategic
These initiatives not only streamlined operations but also fortified our data Planning, Agile Methodologies,
infrastructure, enabling more sophisticated and reliable data utilization across Stakeholder Communication, and
the organization. fostering Innovation
Prime Software House July 2010 - May 2012
Associate Data Engineer Certifications:
In my role, I enhanced data management systems by developing optimized data AWS Certified Solutions Architect
models and databases that significantly improved data storage and retrieval for Google Cloud Certified
high-volume transactional data. My work also involved upgrading analytical Professional Data Engineer
platforms by integrating new data sources and refining ETL processes, which Certified Data Management
led to faster and more accurate financial analyses. I was actively involved in Professional (CDMP)
ensuring the accuracy and integrity of financial reports through stringent data
validation protocols. Professional Affiliations:
Simultaneously, I focused on advancing our technological capabilities by: Data Management Association
Building a distributed system using Hadoop and Spark to expedite the International (DAMA)
analysis of call detail records, greatly enhancing our data analysis speed. Association for Computing
Creating APIs that improved data accessibility and integration, making it Machinery (ACM)
easier to ingest and analyze data across systems. Society for Industrial and Applied
Automating infrastructure deployment using CloudFormation, which Mathematics (SIAM)
ensured consistency and reliability across our environments.
Fine-tuning scalability and performance to handle large volumes of data,
significantly boosting system performance and reliability.
These efforts not only improved our day-to-day operations but also set new
standards for data processing and analysis within the organization, reflecting
my commitment to continuous improvement and operational excellence.
EDUCATION
BS Computer Science Sep 2006 - Jun 2010
New York University (NYU)
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