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Nasir Zia

@nasirzia

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Senior Data Engineer with 8+ years of experience in data solutions.

Zimbabwe

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What I'm looking for

I am looking for a role that challenges my skills and fosters growth in a collaborative environment.

I am a Senior Data Engineer with over 8 years of experience in designing and implementing data solutions across Azure and AWS for clients such as Southwest Airlines and Best Buy. My journey has been marked by significant achievements, including improving data retrieval accuracy to 90% through a pioneering Python script now utilized by a team of 10 data scientists. I have constructed over 10 production-ready data pipelines leveraging technologies like Spark, Kafka, and Hive, achieving an impressive 99.9% data uptime.

Throughout my career, I have been recognized for my fast progression, having been promoted four times in five years from a data analyst to a senior data engineer. My expertise lies in orchestrating data pipelines, enhancing data governance, and ensuring data quality across various platforms. I thrive in environments that challenge my skills and allow me to contribute to impactful data-driven decisions.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Southwest Airlines

Apr 2024 - Present (1 year 2 months)

Pioneered data pipelines within Azure Data Factory, interfacing with Snowflake and Azure SQL, sustaining 10+ daily reports and resolving 95% of data integration incidents. Configured Azure Data Factory pipelines with Linked Services, Datasets, and triggers to streamline data integration, reducing manual effort by 15 hours/week.

Azure Data Factory Snowflake Azure SQL Git Azure DevOps Apache Spark Power BI SQL Python

Data Engineer

Best Buy

May 2023 - Mar 2024 (10 months)

Transformed complex SQL queries into PySpark using Spark DataFrames and Python, enhancing data processing efficiency and scalability. Refactored and modernized legacy Informatica ETL processes into Apache Airflow DAGs, enhancing data pipeline resilience and cutting down on data defects to less than 0.01%.

Pyspark DataFrames Informatica Apache Airflow Apache Kafka Databricks Python SQL

AWS Data Engineer

Chapman University

Jul 2021 - Apr 2023 (1 year 9 months)

Delivered a petabyte-scale Enterprise Data Lake on AWS with S3, Glue, Redshift, and Athena, slashing data processing times by 60% and enabling real-time reporting dashboards. Launched data ingestion pipelines in AWS Glue Studio to process data from diverse sources and constructed interactive business intelligence dashboards in QuickSight.

AWS S3 AWS Glue AWS RedShift QuickSight AWS Lambda Apache Airflow Terraform SQL Python

Big Data Engineer

Barings

Sep 2019 - Jul 2021 (1 year 10 months)

Piloted five high-throughput data pipelines using Python and cloud-based technologies, accelerating data processing speeds and reducing infrastructure costs by 30%. Orchestrated ETL processes, converting raw data into usable insights, resolving 90% of data quality issues, and achieving a 99.9% data availability rate.

Python Apache Spark Hive HDFS Oozie Pig Kafka SSIS SQL ETL

Data Analyst

GAF-Roofing-Manth

Jul 2018 - Aug 2019 (1 year 1 month)

Automated 90% of manual data validation processes, increasing data accuracy by 25% and freeing up 15 hours per week for the data engineering team. Established data pipelines using Apache Spark on AWS, processing 500+ GB Kinesis streams to S3, enhancing real-time analytics dashboard refresh rates.

Apache Spark AWS Kinesis S3 Snowflake AWS Glue Apache Airflow Azure Data Factory MongoDB MSSQL Power BI

ETL Developer

Atla Med

May 2016 - Jun 2018 (2 years 1 month)

Led full lifecycle data migration from DEV to PROD, executing four mock loads and ensuring a seamless go-live process in S/4 HANA environments. Constructed 10+ PySpark applications that extracted, transformed, and aggregated customer usage data, pinpointing critical churn factors and directly contributing to a 15% reduction in customer attrition.

Pyspark ETL SQL Data Warehousing Data Migration API Integration