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uannabi/README.md

πŸ‘‹ Hi, I’m Zahid

I architect large-scale financial data platforms that power strategy, not just reports.


πŸ† Core Specialities;

Data-as-a-Product Vision Turn raw, disparate events into governed, self-service datasets with clear lineage, SLAs, and docs.
Financial Domain Mastery Premium, Ads & Royalties pipelines that enable revenue analytics, compliance, and real-time insights.
Cloud-Scale Engineering Spark Β· Beam Β· Dataflow on GCP, orchestrated with Airflow and delivered through BigQuery.
Model-Driven Impact Causal inference & predictive models that have lifted engagement +25 % and cut launch cycles –30 %.
Cross-Functional Leadership Bridge Finance ↔ Product ↔ Engineering, mentoring teams in clean code, standards, and data quality.

πŸš€ Mission

To craft foundational, reusable data abstractions that let every squad explore and act with confidenceβ€”transforming messy realities into strategic clarity at global scale.

LinkedIn Medium Kaggle LeetCode

Snake animation

πŸ“ž Let's Connect!

Connect on LinkedIn.

🧰 Tools I've experienced with

Python Badge R Badge Django Badge Scala Badge Pandas Badge Plotly Badge Anaconda Badge Jupyter Badge NumPy Badge Databricks Badge Metabase Badge Docker Badge Kubernetes Badge Git Badge Linux Badge Apache Spark Badge Elastic Search Badge Amazon AWS Badge Google Cloud Badge Google Colab Badge Kaggle Badge Tableau Badge


class DataAnalyticsEngineer:
    def __init__(self, name, degree, languages, tools):
        self.name = name
        self.degree = degree
        self.languages = languages
        self.tools = tools
        self.stakeholders = []

    def introduction(self):
        return f"Here I am, {self. name}, fortified by a robust passion for converting complex data into groundbreaking solutions, all backed by the collaborative and versioning strengths of GitHub."

    def educational_background(self):
        return f"I hold a {self. degree} in Computer Science and Engineering."

    def technical_skills(self):
        languages = ', '.join(self.languages)
        tools = ', '.join(self.tools)
        return f"Further enhanced by a mastery of programming languages like {languages}, and proficient use of cutting-edge analytics tools like {tools}."

    def data_capabilities(self):
        return "My background spans data engineering, predictive analytics, data visualization, and machine learning, proving my ability to turn multifaceted data into compelling narratives and actionable insights."

    def unique_selling_points(self):
        return "What sets me apart is my technical acumen and my deep-rooted understanding of leveraging data as a strategic asset for solving complex business issues and driving informed decisions."

    def collaboration(self):
        stakeholders = ', '.join(self.stakeholders)
        return f"Thriving in collaborative settings, I effortlessly engage with stakeholders at every organizational level: {stakeholders}."

    def ambition(self, organization):
        return f" As a proactive self-starter and an invaluable team player, I am eager to deploy my broad data engineering and analytics skills to elevate {organization} to new heights of excellence."

    def add_stakeholder(self, stakeholder):
        self. stakeholders.append(stakeholder)

    def full_profile(self):
        return f"{self.introduction()}\n{self.educational_background()}\n{self.technical_skills()}\n{self.data_capabilities()}\n{self.unique_selling_points()} \n {self.collaboration()}\n{self.ambition('LSEG')}"

if __name__ == "__main__":
    engineer = DataAnalyticsEngineer(name="Zahid Un Nabi", 
                                     degree="Bachelor's Degree", 
                                     languages=['Python', 'SQL'], 
                                     tools=['Tableau'])

    engineer.add_stakeholder('Business Analysts')
    engineer.add_stakeholder('Data Scientists')
    engineer.add_stakeholder('Product Managers')

    print(engineer.full_profile())

  • πŸ”­ Currently working at Post Trade London Clearing House LSEG
  • 🌱 I’m currently working with a large number of financial data.
  • πŸ‘― No collaboration !=01000101 01001111 01000100
  • πŸ€” I’m looking for 01011111 01011111 01101001 01101110 01101001 01110100 01011111 01011111
  • πŸ’¬ Ask me about 01100100 01100001 01110100 01100001 00100000

Articles on Medium

The first one ABC about Big Data Analysis 5 V for Big Data Analysis

Build your own data lake Data Lake on AWS

ETL explained using aws! ETL Techniques

First Missing Positive Problem-solving

Train your personal AI Model AI Model


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    Machine Learning Algorithm Linear Regression using pySpark

    Jupyter Notebook

  2. PySparkExercise PySparkExercise Public

    Pyspark Basic problem solve using Jupyter Notebook

    Jupyter Notebook 1

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    Sentiment analysis using python

    Python

  4. RxPY RxPY Public

    Forked from ReactiveX/RxPY

    Reactive Extensions for Python

    Python

  5. soul-stone soul-stone Public

    Serverless service using lambda and tweeting stream

    Python

  6. SparkDataFrame SparkDataFrame Public

    Pyspark Dataframe basics

    Jupyter Notebook 1