Senior Data Engineer (12 month contract) - WildRift Data at Riot Games

Sydney, New South Wales, Australia -

Full Time

Start Date

Immediate

Expiry Date

04 Jun, 26

Salary

0.0

Posted On

06 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Platform, Lakehouse, Data Modeling, Data Governance, Scalability, Databricks, Spark, PySpark, SparkSql, Delta Lake, Airflow, Python, Data Quality, Metadata, CI/CD

Industry

Computer Games

Description

Riot's Data Engineers build products that improve the experience of our players worldwide using petabytes of data and state-of-the-art processing technology. Maximizing the potential of this data is a complex task. As a Senior Data Engineer (Contract) joining the Sydney-based team, you will lead the modernization and uplift of our data platform to improve reliability, governance, and scalability. You will drive architectural refactoring across our lakehouse environment, consolidate and standardize data models, and enforce a clear Bronze/Silver/Gold medallion hierarchy. You will implement robust data quality and observability frameworks for business-critical datasets, operationalize data ownership and tiering standards, and elevate metadata completeness and lineage transparency across our data catalog and warehouse ecosystem. Working closely with cross-functional stakeholders, you will help transform the data environment into a trusted, production-grade platform that supports operational decision-making, executive reporting, and advanced analytics. This role is based in Sydney and a 12-month contract. Responsibilities: Partner with senior engineers to execute architectural improvements across the lakehouse platform. Implement dimensional data models and standardize semantic/gold reporting layers. Enforce medallion (Bronze/Silver/Gold) architecture standards. Build and integrate automated data quality monitoring. Improve metadata completeness and lineage transparency through catalog updates and automation. Contribute to CI/CD standards and pipeline reliability improvements. Collaborate with cross-functional stakeholders to deliver production-grade, trusted datasets. Required Qualifications: 5+ years of relevant experience building scalable data platforms in production environments. Strong experience in data modeling and data warehousing, e.g. medallion lakehouse architecture. Strong hands-on expertise with Databricks, Spark (PySpark/SparkSQL), Delta Lake, Airflow, and Python. Experience implementing automated data quality checks and validation frameworks. Experience with dbt or similar transformation frameworks. Experience delivering on AWS-based data platforms. Familiarity with metadata/catalog tools (Atlan, Alation, DataHub, Unity Catalog, etc.). Desired Qualifications: Fluency in Mandarin Chinese is highly desirable. Experience contributing to data platform modernization or data maturity uplift initiatives. Experience working across cross-regional engineering teams. Experience improving metadata automation or lineage tooling. For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role! Riot Games fosters a player and workplace experience that values teamwork embodied by the Summoner's Code and Community Code. Our culture embraces differences as a strength, and our values are the guiding principles for how we approach work. We are committed to putting diversity and inclusion (D&I) at the center of everything we do, and promoting a fair and collaborative culture where Rioters treat one another with dignity and respect. We encourage you to read more about our value of thriving together and our ongoing work to build the most inclusive company in Gaming.

Responsibilities

The Senior Data Engineer will lead the modernization and uplift of the data platform, focusing on improving reliability, governance, and scalability across the lakehouse environment. Responsibilities include driving architectural refactoring, standardizing data models, enforcing medallion hierarchy, and implementing data quality and observability frameworks.