Analytics Lead

  • İstanbul, Turkey
  • Analytics
  • À plein temps
<p><strong>Analytics Lead</strong><strong><br></strong>Location: Istanbul, Turkey</p> <p><strong>Who You’ll Work For </strong></p> <p>REEF transforms Urban Spaces into Community hubs that create jobs and bring new goods, services and experiences to the neighborhood.</p> <p>With an ecosystem of 5,000 locations and a team that’s over 18,000 strong, REEF is the largest operator of parking real estate and delivery restaurants in North America.</p> <p>By connecting the world to your block, we’re making the place you live, the place you love to be.</p> <p><strong>What You’ll Do</strong></p> <p>As an Analytics lead, you will get the exciting opportunity to lead a team of BI Developers and BI Engineers. Your team will be aligned with a specified business unit that you will partner with, to define their data needs and deliver value-adding reporting that enables frictionless decision making.</p> <p>Our team is serious about great design and redefining best practices with a cloud-based approach to scalability and automation. A successful candidate will be a person who enjoys working closely with business stakeholders to define a data roadmap, prioritize immediate needs, dive deep into data analysis, and coordinate the implementation of long-term solutions.</p> <ul> <li>Define and prioritize work for the team, using stakeholder’s input to focus on highest value first.</li> <li>Act as the POC from a data perspective for the business unit the team is supporting.</li> <li>Develop a data roadmap, with continuous improvement in mind.</li> <li>Use your expert SQL and data modeling skills to build the base layer data model that will power Reef’s reporting dashboards</li> <li>Work closely with engineers and business users to troubleshoot and resolve data quality issues and maintain high level of data accuracy</li> <li>Simplify, optimize and document existing code</li> <li>Write ETL jobs to transform data coming from a variety of systems and files into data warehouse</li> <li>Interact with the Data Science, Analytics and Performance team, understand their needs and translate the to a data model</li> <li>Be part of the team responsible for the data architecture and design of the schemas in the data warehouse</li> <li>Think about how you can make end users more productive through self-serve capabilities</li> </ul> <p><strong>What We Want From You:</strong></p> <ul> <li>Bachelor’s degree in a quantitative area such as math, statistics, computer science, engineering, or equivalent experience</li> <li>2+ years of experience working in business intelligence on an enterprise data warehouse team.</li> <li>Ability to define work for team, act as reviewer on team deliverables, coordinate UAT sessions with stakeholders.</li> <li>2+ year leading a team of BI Engineers and BI Developers that service a business organization</li> <li>Advanced using ETL, data modeling, query optimization and SQL skills a business environment with large-scale, complex datasets</li> <li>Knowledge of data warehouse principles and methodologies</li> <li>Experience testing and optimizing ‘big data’ data pipelines, architectures and data sets</li> <li>Good knowledge of Python (PySpark an asset)</li> <li>Strong communication skills and experience in gathering requirements and formulating business metrics for reporting</li> <li>Experience with Cloudera or any Hive database, Java and Rest API an asset</li> <li>Self-driven, highly motivated and able to learn quickly</li> <li>Experience in Tableau or a similar tool is an asset</li> </ul> <p>REEF Technology is an equal opportunity employer, and we value diversity at our company. REEF does not discriminate on the basis of race, religion, color, sex, national origin, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or disability status. REEF complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.&nbsp;</p> <p>&nbsp;</p> <p><strong>&nbsp;</strong></p> <p>&nbsp;</p> <div> <p>&nbsp;</p> </div>

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