Data Engineering Manager

4 weeks ago

Dubai, United Arab Emirates Moove Full time

**About Moove**

**Moove** is on a mission to make the world more productive and successful by redefining access to auto finance and vehicle ownership. Our starting point is a technology-enabled lending model to radically transform the availability of auto finance and vehicles for on-demand mobility marketplaces. By doing so, Moove is creating sustainable jobs for entrepreneurs in the mobility sector.

**The Opportunity**

Building the fintech mobility platform of the future necessitates putting data at the heart of everything we do. To support this mission we are building the Data function composed of Data Science, Engineering, Analytic and Governance subgroupings. All Data team members through their exceptional research and programming skills are pivotal to our business model and will have a terrific opportunity to make their mark.

**About the role**

We are looking for a highly professional, experienced and hands-on Data Engineering Manager who can work in a fast-paced and growing environment and build and manage an effective cross-functional team. You will be leading teams of data engineers to create best-in-class tooling to support data science, machine learning, AI and business intelligence initiatives. You’ll inspire data engineers to engage, learn, and focus on big data technologies. You’ll empower our engineers to dream bigger about what’s possible. You’ll enjoy coaching your teammates, recruiting new team members, and ensuring that we maximise how we think about data.

**Key Responsibilities**
- Manage cross-functional engineers and develop their careers, assigning them to projects tailored to their skill levels, long-term skill development, personalities, and work styles.
- Be responsible for the planning, execution, and success of complex technical projects in a fast-paced environment.
- Partner with key cross-functional teams to increase data quality and trust
- Provide guidance and mentorship to fellow data engineers by disseminating best practices, publishing reusable tools/code and giving constructive feedback.
- Conduct undirected research and frame open-ended industry questions
- Extract data and generate features from multiple internal and external sources
- Employ sophisticated analytics programs, machine learning, and statistical methods to prepare data for use in predictive & prescriptive modelling
- Thoroughly clean and prune data to discard irrelevant information
- Explore and examine data from a variety of angles, extract patterns and determine hidden weaknesses, trends, and/or opportunities
- In charge of the end-to-end data science pipeline (data selection, cleaning, preparation and transformations. Ensemble model generation, model evaluation, and hypothesis refinement)
- Communicate and explain the new findings through effective data visualizations and storytelling

**Key Requirements**
- 3+ years of management experience with proven leadership skills in building and scaling cross-functional teams, people management, people growth and stakeholder management
- An advanced degree in a quantitative field - mathematics, physics, computer science, engineering, statistics, operations research, economics, related degree, or equivalent practical experience.
- Experience in aligning with other teams on defining scope, domain boundaries and dependencies
- Knowledge of scalable data models that address a wide variety of consumption patterns including random-access, and sequential access including necessary optimizations like bucketing, aggregating, and sharding.
- Solid understanding of Data Governance, Data Security, Data Cataloguing and Data Lineage concepts
- Consistent record of leading and influencing projects using data and working with large-scale data and infrastructure
- Experience in Big Data platforms such as Spark is a big plus.
- Experience with data visualization tools (D3.js, Tableau, QuickSight,)
- Experience in Information Retrieval and building end-to-end Machine Learning models (e.g., random forests, gradient-boosted trees, neural networks, survival models, Bayesian inference, k-means clustering, and deep learning) and optimization techniques (e.g., gradient descent, genetic algorithms).
- Knowledge of Natural Language Processing, Image Processing and Signal Processing
- Experience in probabilistic programming languages (e.g., Stan, JAGS) and web programming languages (e.g., Python, Node.js, PHP, Ruby, Go)
- Comfortable with working with multiple stakeholders in a multi-cultural environment of a global matrix organization with sensitivity and partnering
- DevOps/DataOps skills are plus points
- Experience as a product manager in this field is a plus

**Who You'll Be Working with**:
Directly reporting to our Head of Data, and closely working with our Data Engineering Team.

**About the team**

Our team is collaborative, positive, curious, and engaged. We think fast, work smart, laugh often, and are looking for like-minded people to join us in our mission to disrup

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