Position: Data Engineer / ETL Developer
Company: Woxlab
Experience required: 3y
English level: intermediate

**About Untapped**

Untapped Global is an investment and technology company based in the US, with offices and representatives in Kenya and South Africa. Its mission is to bridge the investment gap in emerging markets, by radically changing the risk profile of debt investment in these countries for everyday investors. To do so, Untapped has developed a Smart Asset Financing technology and investment vehicle. It leverages technology to collect data about its financial and social impact and provides near real-time portfolio performance data to its investors.

**About the role**

As we scale up, we are looking for a savvy Data Engineer to join our growing team. In this role, you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection from our third-party operating partners. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, product managers, and investment officers on data integration and data architecture initiatives and will ensure optimal data delivery architecture is consistent and efficient across the organization.

**Key duties and responsibilities:**

● Create and maintain optimal data pipeline, data lake, and data warehouse architecture as aligned with Untapped’s business requirements

● Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability, availability and/or usability

● Ensure optimal database architecture to avoid database redundancies, to optimize performance, and to ensure that the database is logical as regards Untapped’s business model

● Build and/or configure the infrastructure required for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources using SQL and modern “big data” technologies

● Build analytics tools that utilize the data pipeline to provide actionable insights into asset performance, operational efficiency, and other key portfolio and business performance metrics

● Implement data quality monitors and alerts to proactively identify data cleanliness issues or anomalies

● Work with stakeholders including the Executive, Product, Engineering, and Design teams to assist with data-related technical issues and support company-wide data infrastructure needs

 ● Maintain backups of data lake and data warehouse in a highly secure, scalable, and available environment (currently hosted on AWS)

● Create data tools for analytics and data scientist team members that assist them in building and optimizing models to drive business growth

**What you will bring to Untapped:**

✔ Bachelor’s degree in Computer Science (CS), Statistics, Informatics, Information Systems, or related quantitative field - equivalent industry experience and demonstrable knowledge may be used to replace this requirement

✔ 3+ years of experience in data engineering role, building and optimizing data pipelines, architectures, and datasets

✔ Strong experience in data modelling and ETLs using SQL and Python (Pandas, pygrametl, petl, SciPy)

✔ Strong analytic skills related to working with structured and unstructured datasets

✔ A history of building processes and tools supporting data transformation, data structures, metadata tagging, dependency, and workload management

✔ Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

✔ Experience supporting and working with cross-functional teams in a dynamic startup environment, bonus if the experience is in Africa

✔ Experience with relational SQL databases, specifically PostgreSQL

✔ Experience working with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, NiFi, etc.

✔ Experience with AWS cloud services, such as EC2 and RDS (EMR and Redshift are bonus)

✔ Optional: experience with NoSQL databases, for example MongoDB and Cassandra

✔ Optional: experience working with big data tools: Hadoop, Spark, Kafka, etc.

✔ Optional: experience with stream-processing systems: Storm, Spark-Streaming, etc.

✔ Optional: experience web scraping: Scrapy, BeautifulSoup, etc.

✔ Optional: interest in Data Science and experience with frameworks such as: SciKit-Learn, Keras, TensorFlow, etc.