Wheely is a premium-only ride-hailing service from Moscow that recently expanded to London. Our most basic service starts with executive (Mercedes E-Class or similar) and ends with ultra-luxury (Mercedes-Maybach). We are doing $50m in annual gross bookings & growing 100% YoY. Ride-hailers are emerging either as local champions or niche players, and our goal is to build the #1 premium ride-hailing in Tier 1 cities.
We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. 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 DataOps will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
- Create and maintain optimal data pipeline architecture;
- Assemble large, complex data sets that meet functional / non-functional business requirements;
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.;
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies;
- 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 stakeholders including the Executive, Product and Marketing teams to assist with data-related technical issues and support their data infrastructure needs;
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader;
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases;
- Experience building and optimizing ‘big data’ data pipelines, architectures;
- Build processes supporting data transformation, data structures, metadata, dependency and workload management;
- A successful history of manipulating, processing and extracting value from large disconnected datasets;
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores;
- Strong project management and organizational skills;
- Experience supporting and working with cross-functional teams in a dynamic environment;
- Strong automation skills (tool agnostic);
- The ability to design, build, and operate a technology stack;
- Configuration and automation management, health checks, single point of failure, notifications.
TOOLS & lANGUAGE EXPERTISE
- Expert skill in the following or similar tools: Docker, Jenkins, Swagger, Git, traefik/Nginx, Flask/Falcon/other REST API service;
- Expert skills in MongoDB (or other NoSQL DB) and Redshift (or other PostgreSQL);
- Strong operational experience in Linux/Unix environment and scripting languages: Shell, Perl, Python.
- We’re a well-funded and rapidly growing start-up scaling up in new markets;
- You’ll have real impact in revolutionising the transportation industry;
- Wheely rides to test everything first hand;
- Our culture is energetic and entrepreneurial: we’re passionate about enabling everyone to have impact on the company’s growth and evolution, and having a lot of fun along the way;
- Employee Stock Option program;
- Flexible working hours;
- Health insurance after probation period, including medical, dental and travel;
- We'll ensure you have the best tools money can buy. MacBook Pro Retina is a standard issue;
- Monthly stipend for courses and education (e.g. books, Datacamp, Dataquest, etc..);
- Сoffee, fruits, snacks and free lunches.