Senior Analytics Engineer (AI Data Engineer) - 153649-1

About the job Senior Analytics Engineer (AI Data Engineer) - 153649-1

Job Title: Senior Analytics Engineer (AI Data Engineer) - 153649-1

Candidates with previous experience working at Microsoft Corporation, either as a full-time employee (FTE) or contractor, are strongly preferred.

Summary

Join us as a Senior Analytics Engineer and be an architect of our data-driven future. We are seeking a strategic thinker who will combine their technical expertise with a deep understanding of the business to deliver solutions which transform raw gaming data into actionable insights and data products.

You will build robust pipelines, well-crafted data models, and innovative data products to drive impactful outcomes. You will prioritize security, data quality, reliability, and usability to ensure stakeholder confidence in our solutions. To be successful, we collaborate with data scientists, analysts, data engineers, game teams and stakeholders at the pace of our business.

Our team is passionate about our mission, embracing challenges with a growth mindset, and continuously leveling-up.

Typical Day in the Role

Purpose of the Team: 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 a Senior Analytics Engineer to join the Minecraft data and analytics team and help us shape the future of Minecraft at Mojang Studios.

Key projects: The team is focused on building an analytics environment for Minecraft, specifically within the Minecraft studio. This involves shaping, curating, and transforming data into models and structures suitable for analytics. This senior analytics engineer will work closely with data scientists to meet their information needs, ensuring the data is designed and shaped appropriately for their use.

Job Requirements

• Build subject matter expertise of our business and data domains to collaborate with data consumers and stakeholders to understand their information needs and assist them with data access.
• Identify and analyze multi-structured data or metadata from a variety of sources to select and document the most effective and accurate data which fulfills the analytics requirements.
• Design data models, architect dataflows, and develop abstractions to deliver scalable solutions for analytics and machine learning ensuring they can evolve with changing needs.
• Leverage modern data engineering practices and frameworks with an object-oriented approach to architect, build, and maintain automated data pipelines which transform data into clean, enriched, and accurate information.
• Advance our infrastructure by developing frameworks, reusable components and new capabilities to achieve our mission.
• Steward the creation, collection, maintenance, and management of metadata.
• Handle confidential information responsibly and correctly apply security and privacy policies.
• Test programs or databases, correct errors and make necessary modifications

Candidate Requirements

• Years of Experience Required: 3-5 overall years of experience in the field. In a data analytics, 5-7 in the engineering space. 3-5 in data engineering
• Degrees or certifications required: Software engineering degree or equivalent.

Disqualifiers: This is NOT a true Data Scientist role - candidates submitted with only data scientist experience will be Disqualified. Please review the JD thoroughly.

Industry mismatch.

• Data experience is not relevant.
• 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 concrete examples.
• Lacks critical thinking skills.

Best vs. Average: The ideal candidate has previous experience with DataBricks. The ideal candidate has experience with analytics engineering with an emphasis on understanding the business's information needs and why this data needs to be prepared in a specific way, moving data, and checking for quality.

Additional preferences include video game domain knowledge, great quality of work as related to the usability by our analysis and user, and previous experience with AI.

Candidate is a critical thinker who has a solid track record building Big Data Pipelines. Strong Python skills and a pythonic mindset to create efficient and effective Python code. Highly usable and effective data models. Good collaborator and communicator with project partners and stakeholders.

Qualifications

• Bachelor's degree in a technical field such as computer science, computer engineering or related field required
• 5-7 years applicable experience required
• Critical thinker and problem solver who brings a creative and open mindset to each situation.
• A proven track record building and optimizing analytic solutions and data products which deliver significant business impact.
• Data analysis and exploration skills to identify, select and prepare data or metadata for analytics.
• Business acumen to understand and address business challenges through analytics engineering.
• Experience building, maintaining and optimizing enterprise scale data pipelines handling logs and event streaming data on Cloud Data Platforms using modern tools like Spark, and airflow; Azure preferred.
• Strong Python skills for data processing combined with a pythonic mindset. Proficient SQL.
• Working knowledge of DevOps and DataOps.
• Video game domain knowledge is important as an experienced Player or industry veteran.

Top 3 Hard Skills Required + Years of Experience

• Python | 3 5 Years of Experience
• SQL | 2+ Years of Experience
• Data modeling | 3 5 Years of Experience
• Big data pipelines | 5 Years of Experience
• Cloud experience| 3 5 Years of Experience

Hard Skills Assessments

• Expected Dates that Hard Skills Assessments will be scheduled: ASAP
• Hard Skills Assessment Process: The assessment process will include 2 rounds, a 45 minute HSA with the sponsor, and a final HSA with a team member or the sponsors manager. May involve a data engineering skills test.
• Required Candidate Preparation: Candidates should be prepared to demonstrate knowledge of data engineering frameworks and methodologies, as well as demonstrate knowledge of cloud services and solution architecture for analytics solutions.