Data Engineer III with experience in data engineering, ETL, data pipelines, QA automation, and cloud-based data infrastructure. Experienced in Python, SQL, SAS, DBT, AWS, Snowflake, BigQuery, Git, Jira, Looker, Tableau, …
Data Engineer III with experience in data engineering, ETL, data pipelines, QA automation, and cloud-based data infrastructure. Experienced in Python, SQL, SAS, DBT, AWS, Snowflake, BigQuery, Git, Jira, Looker, Tableau, and Airflow, with a background in machine learning and predictive modeling.
+ Collaborated with a small team to create and manage 16 different data pipelines and provide clean real-time
inventory and financial data to the analytics and executive team.
+ Successfully refactored 16 diverse data pipelines within a defined time-frame, transitioning from an obsolete CDC
platform to a new CDC solution
+ Implemented automated alerts and standardized error-handling protocols, enhancing data quality and pipeline
efficiency.
+ Ensured data quality and pipeline efficiency by implementing automated alerts and standard procedures for error
resolution.
+ Collaborated cross-functionally via Git, conducting rigorous code reviews and ensuring version control alignment.
+ Leveraged DBT to stage raw data, optimizing data warehouse utilization and scheduling Looker models for real-time
insights.
+ Used Jira to facilitate seamless project management and stakeholder engagement, fostering cohesive communication
channels.
Collaborated with a small team to create and manage 16 different data pipelines and provide clean real-time inventory and financial data to the analytics and executive team.
Successfully refactored 16 diverse data pipelines within a defined time-frame, transitioning from an obsolete CDC platform to a new CDC solution.
Implemented automated alerts and standardized error-handling protocols, enhancing data quality and pipeline efficiency.
Ensured data quality and pipeline efficiency by implementing automated alerts and standard procedures for error resolution.
Collaborated cross-functionally via Git, conducting rigorous code reviews and ensuring version control alignment.
Leveraged DBT to stage raw data, optimizing data warehouse utilization and scheduling Looker models for real-time insights.
Used Jira to facilitate seamless project management and stakeholder engagement, fostering cohesive communication channels.
Led data engineering and development efforts to clean and integrate disparate data sources, providing efficient and scalable automation solutions to Merkle’s fastest growing client.
Automated QA for each step of the ETL process, detecting and alerting potential errors in real-time.
Parsed highly variable client data and designed infrastructure to append multiple sources of data to the customer file.
Successfully migrated data infrastructure from legacy solutions to cloud-based solutions.
Implemented predictive models and performed monthly model scoring using evolving data sets.
Optimized ETL procedures and QA, including overhauling legacy code to reduce a monthly computation time from 6 days to 2 hours.
Developed and maintained data pipelines from multiple sources, cleaning and processing data sets containing up to 250 million observations.
Leveraged supervised and unsupervised machine learning techniques to build customer profiles and generate predictive models for response rates, providing actionable insights to the team.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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