- Experience
- 6–10 yrs
- Salary
- —
- Openings
- 1
- Posted
- 1 week ago
- Work mode
- In office
- Resume
- Required to apply
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Job description
About the Company
Established in 2017, Coffee Beans is specialised in delivering premium consulting services across technology, product development, and business process improvement. The company aids clients in attaining enhanced delivery quality through impactful product launches, simplified processes, and capability building that advances business outcomes in various industries. Leveraging modern technologies, Coffee Beans supports clients in creating superior products and realising enhanced customer value. Additionally, it provides data-driven and AI-powered solutions serving multiple product categories and service domains.
Role Summary
We are looking for a seasoned Data Engineer with 6 to 10 years of experience to join our data team. The chosen candidate will be accountable for architecting, constructing, and sustaining scalable data pipelines and platforms that facilitate advanced analytics and data-informed decision-making across the organisation.
Key Responsibilities
- Design, develop, and maintain robust, scalable, and efficient data pipelines utilizing contemporary data engineering tools and best practices.
- Create and optimize data workflows connecting numerous internal and external data sources and targets.
- Establish and uphold data quality controls, monitoring mechanisms, and alerting protocols.
- Develop efficient and maintainable code abiding by established coding standards and practices.
- Engage in code reviews and contribute actively to technical documentation.
- Diagnose and resolve issues related to data pipelines and performance constraints.
Technical Requirements
- Proficient expertise in SQL with strong data modeling capabilities.
- Hands-on programming experience in Python or Java.
- Demonstrable experience using Apache Spark for processing large-scale datasets.
- Experience managing workflow orchestration via Apache Airflow.
- Familiarity with contemporary data platforms and warehouses particularly Databricks and/or Snowflake; certifications in Snowflake or Databricks are advantageous.
- Experience operating with at least one leading cloud service provider among AWS, Google Cloud Platform, or Microsoft Azure.
- Solid understanding of data engineering frameworks, ETL processes, and principles of data warehousing.
Level
Lead
Industry
Management Consulting