Data Engineer at FairMoney

Requirements

Roles and Responsibilities

As a Data Engineer at FairMoney, you will be responsible for mainly, but not limited to:

• Work closely with Data Analysts/Scientists, understand the business problems, and translate the requirements into a database, ETL, or reporting solution.
• Design, build, and maintain integration of heterogeneous data sources for DW & BI solutions to simplify analysis across the products.
• Design and implement data models aligning with business needs and supporting best practices in data warehousing.
• Contribute to the ongoing development and optimization of the data warehouse architecture.
• Implement tools and processes for ensuring data quality, and freshness with reliable, versioned, and scalable solutions.
• Identify issues in data flow and improvements in data stack which comprises visualization tools (Tableau), data warehouse (BigQuery), data modeling (dbt), git, and other in-house built as well as open source tools.
• Implement best practices for indexing, partitioning, and query optimization.
• Stay up-to-date with new technologies in Data Engineering, Analytics, and Data Science.
• Implementing new technologies in a production environment to create a frictionless platform for data analytics and science teams to reduce turnaround time from raw data to insights and ML training/serving
• Make it easy for business stakeholders to get a better understanding of data, and make the organization data-literate for self-serve analytics.

Requirements

• 3+ years of work experience in designing, developing & maintaining ETL, databases & OLAP Schema, and Public Objects (Attributes, Facts, Metrics, etc.)
• Hands-on experience in designing and implementing data ingestion/integration processes using SQL/Python.
• Strong proficiency in SQL and experience with database systems (e.g., PostgreSQL, MySQL, or similar)
• Proficient in developing automated workflows using Airflow or similar tools.
• Proficiency in data principles, system and architecture, dimensional data modeling for Data Warehousing and Business Intelligence, and data governance principles.
• Good to have development experience in building business applications with a good command of Bash, Docker, Kubernetes, and Cloud Platforms.
• Ability to learn new software and technologies quickly to create prototypes for business use cases and make them ready for production.
• Effectively form relationships with the business stakeholders to help with the adoption of data-driven decision-making.
• Excellent problem-solving skills and attention to detail.