Mamo is on the lookout for a Data Engineer. You will collaborate with cross-functional teams to define, measure and comprehend key metrics, shape business strategy and product roadmap through data.
You will collaborate closely with the product and engineering teams, as well as other stakeholders, to determine data collection requirements, design data schemas, and identify necessary data analysis processes. A key responsibility will be setting up dashboards and generating reports to enable teams to make sound, data-driven decisions. Additionally, you will be responsible for building and maintaining all data pipelines.
Ready to shape the future with data?
What you will do
Analyze large-scale structured and unstructured datasets using analytical, statistical, machine learning, or deep learning techniques to address a wide range of complex issues.
Collaborate with stakeholders from various departments to comprehend their business requirements and obstacles, design and develop analytics solutions to achieve business goals, and facilitate decision-making.
Partner with cross-functional teams to provide strategies based on data-driven insights across product, marketing, compliance, and other areas.
Identify, understand, and evaluate external/internal opportunities to enhance our products and services.
Determine and assess the success of product initiatives through goal setting, forecasting, and monitoring of key product metrics.
Create data models, data automation systems, performance metrics, and reporting frameworks, and monitor impact over time.
Present results and business impacts of insight initiatives to stakeholders within and outside of the organization.
What we're looking for
Adept at dissecting vague and high-level problems and coming up with solutions.
Skilled in data extraction, analysis, and/or modeling.
Capable of working autonomously, with minimal supervision, in a dynamic environment.
Self-motivated, creative, team-oriented, with strong communication and presentation abilities, able to bridge business and technical audiences.
An advocate for documentation, transparent communication, and knowledge sharing.
You have
You have more than 5 years of professional experience with analysis tools and recommendation systems.
Extensive experience in SQL.
Hands-on experience with Looker or similar tools.
Solid experience in Python and data analysis libraries such as pandas, numpy, matplotlib, scikit-learn, etc.
Experience in using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.
Bonus if you have
Payments, Fraud, Risk, E-Commerce or Finance background.
Experience with Looker, BigQuery and other GCP services.
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