• Develop an ETL jobs
• Assures the efficiency of using cluster resources applied to an ETL job
• Design and implements cost-effective framework level big data solutioning
• Provide support on the big data issues encountered on company proprietary enterprise data system and frameworks
• Enhance an ETL job applying best practices and the spark configuration balancing Participates in reviewing project and program logic requirements
• Cascading of macro-change in framework and system to team and other teams working and affected to the job
• Conversion and migration of job from one platform to another big data platform
• Integration of a job from its ingested source transforming it into various target like databases, extracts file and use case of streaming platform
• Maintains and/or handle source core repositories
• Document technical deliverable modules
• Keep technology trends with relation to big data ETL as much as possible
• Work on multiple ETL jobs implementing java-spark, airflow and loading in different data warehouses and for different reports like financial reports, leads reports, network subscriber reports and extracts like cell-site extracts, telcoscore, gscore, etc.
• Troubleshooting, testing and pre-implementing ETL’s data mapping in pyspark
• Work on multiple ETL jobs for Datamart, the data mainly focuses on Globe’s broadband, postpaid and prepaid to reimagine the customer experience for machine learning engineers to use
• Macro-conversion of ETL jobs from running on-premises into all cloud-based and running on cloud-based cluster and bigdata tools
• Develop an ETL jobs for Digital Growth and Transformation use cases to help business envisions the financial summary report and the data use to help track customer’s payment transaction, rewards, subscriptions and gain a macro-view on regional leads
• Use Databricks for the migrations of the other jobs to have control on managing compute usages.
• Applying techniques on spark reading and writing sources and targets to reduce runtime Work on solutioning for cost-effective ETL job implementations together with engineers in data quality and data architect.

Tech skills must-haves:

• ETL & SQL

• Snowflake

• Airflow