We provide simple, affordable health & life insurance to emerging market consumers. Our mission is to free people from the fear of financial shocks.
About the role
We are looking for a Data Engineer who will proactively implement methods to improve data reliability and quality. They will be responsible for coordinating with teams to create unique data infrastructure, running tests on their designs to isolate errors and updating systems and data to accommodate changes in company needs.
Duties & Responsibilities
- Acquire and/or assemble datasets that align with functional / non-functional business needs.
- Create and maintain optimal data pipeline architecture.
- Identify, design, and implement internal data process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Develop algorithms to transform data into useful, actionable information.
- Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
- Build, test, and maintain database pipeline architecture and infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with various stakeholders to assist with data-related technical and infrastructure needs.
- Ensure compliance with data governance and security policies.
- Communicate findings to technical and non-technical stakeholders through various means including visualizations and presentations.
- Explore ways to enhance data quality and reliability.
Qualifications for Data Engineer
- 3+ years of as a data engineer or in a similar role.
- Degree in Computer Science, Statistics, IT, or a similar field; a Master’s is a plus.
- Technical expertise in data models, data mining, and segmentation techniques.
- Knowledge of programming languages (e.g. Java and Python).
- Experience visualizing and presenting data for use by stakeholders using Tableau, D3, matplotlib, ggplot, etc.
- Hands-on experience with database design, advanced working knowledge with SQL, experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Great numerical and analytical skills working with structured and unstructured datasets.
- Strong project management and organizational skills.
- Ability to build processes that support data transformation, workload management, data structures, dependency and metadata.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ stores.
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