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Job Description
The journey began with the introduction of a digital microcredit application exclusively available on Android and iOS devices. Today, FairMoney has significantly expanded its range of services, encompassing a comprehensive suite of financial products, such as current accounts, savings accounts, debit cards, and state-of-the-art POS solutions designed to meet the needs of both merchants and agents.
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.
Qualification
- 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.
Location: Remote.
Apply: DATA ENGINEER
