
Hyacinth Ali
Technology / Internet
About Hyacinth Ali:
I'm a software engineer, who focuses on data engineering, cloud, and backend development. I am always learning to stay abreast with new technologies, and I love designing and implementing software systems, data warehouses, as well as data lakehouses. I have a strong desire to work in an environment that requires data modelling to align with the requirements of the systems. Furthermore, I love to undertake different data engineering tasks to promote the revenue of the enterprise. My latest ETL data pipeline uses Apache Airflow to extract datasets from AWS S3, stages them in Redshift, and transforms data into a set of dimensional tables (Star Schema) to power analytics teams. I am a fast learner, hardworking, dedicated, and passionate about my role(s) at my workplace.
Strong Expertise:
1. Advanced experience in building complex software systems with Data Modelling, Domain Modeling, Test Driven Development (TDD,) and Behaviour Driven Development (BDD) patterns.
2. Experience building ETL pipelines on AWS with S3 and Redshift.
3. Proficient in elicitation, specification, and design of software requirements.
4. Expertise in debugging and fixing issues in complex software systems.
5. Experience with Docker to deploy and then manage web applications on AWS.
6. Advanced analytical, problem-solving, research, documentation, and presentation skills.
7. Over 6-year experience designing, implementing, testing, and maintaining complex software systems.
Some Top Skills:
Domain Modelling, Data Modelling, Java, Python, SQL, Object-Oriented Design, and Test Driven Development.
Experience
I have several years of experience across different fields of software engineering, including but not limited to building web applications, data pipelines, streaming IoT data, and cloud computing. I have over seven years of professional experience building and maintaining complex software systems. I am a dedicated person, and always learning to stay up to date with new technologies
Education
My latest ETL data pipeline project uses Apache Airflow to extract datasets from AWS S3, stages them in Redshift, and transforms data into a set of dimensional tables (Star Schema) to power analytics teams.
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