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Job Location: Bangalore/Bengaluru
As our Senior Data Engineer, you ll be a crucial member of the Financial Services Platform at Gojek. In this role, you ll take the wheel in building and scaling our Data Warehouse foundation that enables and delivers reliable and trustworthy data that affects our internal users, driver-partners, and merchant-partners alike. You ll design, develop, and maintain the services for our data ingestion pipeline, ensuring the data is understandable, usable, and adheres to data governance policies. The folks in the Engineering, Business, Operations, and Data Science teams will be your companions on this ride; they ll provide the data you ll utilize in your daily tasks, while you act as a bridge between them and third parties.
What You Will Do
- Create data ingestion from various sources: RDBMS, Rest API, Kafka, Text File and Spreadsheet
- Design, develop, and maintain the services for the data ingestion pipeline; debug any data issues that may arise
- Deploy the data pipeline following data governance and data security requirements, and implement it with the data quality check on Google Cloud Platform
- Provide expert advice on data infrastructure, data architecture, and data modeling to your teammates
- Manage the auto-scaling and performance monitoring of the Infrastructure using Prometheus, Grafana, or similar tools
- Liaise with other Data teams within the Financial Services platform and GoTo company – such as the Data Science, Data Engineering, Data Governance, and Risk Analytics teams – to ensure that initiatives are aligned and data integrity standards are adhered to
- Drive the prioritization, strategy, and focus to solve user problems
What You Will Need
- At least 5+ years of experience in data engineering, BI engineering, and data warehouse development
- Excellent command of programming languages, preferably in Python and Bash; knowledge of Java and Go is a plus
- Experience in managing a serverless data warehouse like BigQuery or Redshift
- Prior DevOps experience implementing large scale data stacks using any CI/CD tool and Docker
- Familiarity with schedulers like AirflowExperience in Kafka, Flink, and Spark is a plus
- Excellent spoken and written skills in English in order to communicate with stakeholders of various backgrounds, and with our international teams
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