Aysha Zenab Kenza
@ayshazenabkenza
Results-driven software engineer specializing in data engineering, scalable pipelines, and analytics-driven solutions.
What I'm looking for
I am a results-driven software engineer with strong expertise in data engineering, analytics, and distributed processing using SQL, Python, Spark, Databricks, and Azure services. I have delivered measurable performance and reliability improvements—reducing pipeline runtimes, resolving schema drift, and optimizing large-scale ETL jobs—while mentoring teammates and authoring technical documentation to onboard engineers and clarify workflows for stakeholders.
My background includes building production Spark pipelines at scale, automating data extraction and triage tooling, and applying statistical and machine-learning methods in clinical research contexts. I thrive in cross-functional agile teams, focus on customer-facing outcomes, and seek to drive impact through performant, maintainable data infrastructure and clear stakeholder communication.
Experience
Work history, roles, and key accomplishments
Own and maintain end-to-end Spark Databricks pipelines orchestrated via Azure Data Factory to process messaging and subscription data; optimized pipelines to cut nightly runtime by 95% on 1B+ rows and improved SLA delivery by 89%.
Software Engineer
Meta Platforms
Feb 2022 - Jan 2023 (11 months)
Built Spark–Python data pipelines and tools to automate user data extraction and unified multi-source datasets, improving backend performance by 10% and reducing MTTR by 40% with a triage CLI.
Data Coordinator
Harvard Medical School
Sep 2021 - Feb 2022 (5 months)
Processed and analyzed 21K+ anesthesia patient records using R and Python, performing logistic regression and tree-based models to identify respiratory risk factors and support peer-reviewed publication.
Data Analyst
Brigham and Women's Hospital
Nov 2019 - Dec 2020 (1 year 1 month)
Built Python tools to extract and structure MRI signals and applied ML to IBD patient data, enabling researchers to use processed datasets for ML-based clinical studies and insights.
Education
Degrees, certifications, and relevant coursework
Boston University
Master of Science, Computer Science
2019 - 2021
Grade: 3.83 / 4.00
Activities and societies: Received scholarship to attend Grace Hopper Women’s Conference 2020; presented a paper at ICETIETR 2018 (IEEE).
Completed a Master of Science in Computer Science with coursework in data science, AI, software engineering, algorithms, web mining, and graph analytics.
Availability
Location
Authorized to work in
Job categories
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