Aspiring Data Analyst with Engineering Background
🔍 With a keen eye for detail and a robust analytical background, I am transitioning from engineering to data analysis, driven by a passion for insightful data-driven deci…
Aspiring Data Analyst with Engineering Background
🔍 With a keen eye for detail and a robust analytical background, I am transitioning from engineering to data analysis, driven by a passion for insightful data-driven decision-making. Based in Abu Dhabi, my tech career began at TCS, engaging with various data-oriented projects, enhancing my experience in PostgreSQL, Python, and cloud technologies.
Following a comprehensive Data Analytics course, I am well-versed in tools like Tableau, Power BI, MySQL, and Excel, all of which fortify my ability to scrutinize and manage data effectively. My aim is to integrate seamlessly into a data analyst role where my analytical prowess and problem-solving skills can thrive.
Curious about my transition and how I could contribute to your data challenges? I’m just a message away from a productive conversation!
Worked across three enterprise-scale projects with expertise in cloud platforms, data engineering, and automation.• Executed batch processing workflows using Jenkins, managing job triggers and artifact retrieval.• Monitored AWS services, including CloudWatch, to oversee batch runs and analyze error logs, ensuring seamless operations.• Developed and optimized PostgreSQL queries to extract actionable insights from transactional datasets.• Leveraged GCP services such as BigQuery, Cloud Functions, and Cloud Storage to process and analyze large-scale data, including appending new data to existing datasets.• Translated complex SAS code into Python, utilizing libraries like pandas, numpy, and xlsxwriter and automated report generation processes
Transitioned complex SAS scripts to Python, implementing automation with libraries such as pandas, numpy, and xlsxwriter. Validated Python-generated reports against legacy SAS outputs and contributed to collaborative development via GitHub, employing various GCP services.
Utilized Google Cloud Platform (GCP) services, including BigQuery, Cloud Functions, Cloud Storage, and Compute Engine, to process and manage large datasets. Conducted testing and validation of Looker dashboards, and crafted SQL queries tailored to client reporting requirements.
Managed batch pipelines using Jenkins and AWS CloudWatch to monitor and troubleshoot rental transactions. Developed optimized PostgreSQL queries for in-depth rental data analysis, ensuring smooth data workflows and accurate reporting.
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