Detail-oriented data engineer with 2 years and 6 months of experience specializing in Google Cloud Platform (GCP). Proficient in designing, implementing and optimizing data pipelines on GCP. Skilled in data ingestion, tr…
Detail-oriented data engineer with 2 years and 6 months of experience specializing in Google Cloud Platform (GCP). Proficient in designing, implementing and optimizing data pipelines on GCP. Skilled in data ingestion, transformation, and storage using GCP services, ensuring reliability and scalability. Strong problem-solving skills with a proven track record of delivering data solutions that drive business insights and efficiency.
Hands-on experience on Google Cloud Platform (GCP) in the GCP Services Big Query, Cloud Dataflow, Google Cloud Storage, Composer (Air Flow as a service), Cloud Scheduler, Python, Unix, and service now.
Skilled at extracting, transforming and loading (ETL) data into a data warehouse from SAP BW source.
Strong SQL development skills including writing build. SQL.
• Played a key role in the development and maintenance of a robust data pipeline on GCP.
• Create a new cloud function using Python to handle errors in data source CSV files.
• Collaborating with the data science and data analyst teams to design and optimize data models and existing SQL logic.
• Proactively established alerts for job failures and files with bad record errors within the GCP.
• Implemented GPOP in Looker and developed critical table check queries and a list of unused table queries.
• Demonstrated exceptional problem-solving skills by effectively debugging and investigating
Production issues, resolving them within specified timelines and conducting a thorough root cause analysis to prevent recurrence.
Managed the integration of various data sources including customer, transaction, inventory, open order, region-based forecast, and financial data.
Oversaw data extraction from SAP BW, SAP ECC, SAP SD, SAP MM, Navision, and Hyperion systems.
Implemented data transformation processes to ensure accuracy before loading into target systems.
Played a key role in the development and maintenance of a robust data pipeline on GCP.
Created a new cloud function using Python to handle errors in data source CSV files.
Collaborated with the data science and data analyst teams to design and optimize data models and existing SQL logic.
Proactively established alerts for job failures and files with bad record errors within GCP.
Implemented GPOP in Looker and developed critical table check queries and a list of unused table queries.
Debugged and investigated production issues, resolving them within specified timelines.
Conducted root cause analysis to prevent recurrence.
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