BS in Software Engineering with experience in data engineering and data analytics. Worked on building scalable data pipelines, analyzing large datasets, and creating reports and dashboards using SQL, Excel, Python, AWS, …
BS in Software Engineering with experience in data engineering and data analytics. Worked on building scalable data pipelines, analyzing large datasets, and creating reports and dashboards using SQL, Excel, Python, AWS, GCP, BigQuery, and Streamlit.
As a data engineer, I'm tasked with designing, building, and maintaining the infrastructure vital for efficient data processing and analysis. This includes developing robust data pipelines using tools like Apache Spark and Airflow to load data from various sources such as AWS S3 buckets and Google Cloud Storage (GCS) into BigQuery for analysis. I also specialize in implementing change data capture (CDC) mechanisms to ensure real-time data updates. Performance optimization is a constant focus, where I monitor pipelines, tune configurations, and leverage caching mechanisms to enhance efficiency. Collaboration is integral as I work closely with stakeholders, including data scientists and analysts, to understand their needs and provide the necessary infrastructure for informed decision-making. In summary, my role revolves around building and maintaining a scalable data infrastructure that empowers organizations to derive actionable insights.
Built and maintained scalable data pipelines for data extraction, transformation, and analysis.
Utilized diverse data tools and cloud platforms (AWS, GCP) to manage and analyze data from various sources.
Analyzed large datasets (SQL, Excel, Python) to uncover trends and inform business decisions.
Developed data-driven reports and dashboards for KPI tracking and stakeholder communication.
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