Candidate Requirement:
• Years of Experience Required –
o 3-5 years.
o The kind of experience is important – Data engineer experience working with the business, experience with video games or something similar, working with a lot of streaming data. Can have that kind of experience that can transfer to this space.
• Degrees or certifications required – Software engineering or equivalent.
• Disqualifiers –
o Industry mismatch.
o Data experience that is not relevant.
o Just using buzz words and not able to demonstrate how they can apply the skills or how they are involved in the experience they are mentioning, need concreate examples.
• Best vs. Average – Quality of work as related to the usability by our analysis and user.
Top 3 Skills:
1. Sequel and data manipulation scripting | 3 – 5 Years of Experience
2. Data modeling | 3 – 5 Years of Experience
3. Big data pipelines | 5 Years of Experience
4. Cloud experience| 3 – 5 Years of Experience
Job Description:
Position: Data Scientist 4
Minecraft is one of the most popular video games of all time, with more than 200 million copies sold worldwide on PC, console, and mobile. Minecraft inspires people around the world to create together and has resulted in one of the most active and passionate player communities in history. We are looking for an Analytics Engineer to join the Minecraft data and analytics team and help us shape the future of Minecraft at Mojang Studios.
As an Analytics Engineer, reporting to the Analytics Environment Manager, you will be responsible to build, optimize and maintain data pipelines for the Minecraft Analytics Environment. In collaboration with Data Scientists, Analysts, Data Engineers, and Architects, you will select, prepare, and shape the data for use in business analysis, reporting, and Machine Learning models. You are focused on delivering solutions rather than technology to realize the value of our data assets. You will support initiatives to democratize data and unlock self-serve capabilities for stakeholders across the studio, empowering all data consumers to efficiently answer analytics questions.
Responsibilities
• Identify and analyze multi-structured data from a variety of sources to assess its effectiveness and accuracy to meet analytics requirements.
• Build and maintain automated data pipelines to transform data into clean, enriched, and highly optimized datasets which fulfil analytic requirements.
• Use modern data engineering practices and frameworks to create scalable big data solutions for analytics and machine learning, while ensuring data quality
• Design, build, and maintain flexible polyglot data models which evolve with user needs.
• Provide stewardship in the creation, collection, and maintenance of metadata.
• Collaborate with data engineers, data scientists, analysts, partners, and stakeholders.
• Provide data access tools for users to unlock the value of the platform’s data.
• Contribute to the design, development, testing and maintenance of data architectures and infrastructure.
• Handle confidential information responsibly and correctly apply security and privacy policies.
• Create documentation and support stakeholders with their understanding and use of the data.
Qualifications
• 3+ year working as a Data or Analytics Engineer or equivalent on large enterprise systems.
• Established data analysis skills to identify, select and prepare quality data for analytics use cases.
• A proven track record building and optimizing big data pipelines for analytic solutions.
• Experience deploying ELT/ETL processes and frameworks with Cloud Platforms; Azure preferred.
• Sound knowledge of data management practices with operational experience on Databricks, Azure Synapse or similar data platforms.
• Advanced SQL skills and proficiency with Python for data processing (PySpark experience a plus)
• Experience with CI/CD, version control and managing production code; ADO an asset.
• Experience integrating data with disparate formats from API, streaming, or other endpoints.
• A sense of personal ownership and accountability while remaining flexible to manage shifting priorities.