Data Ops Engineer

About this role

<p><strong>Who We Are</strong></p> <p>2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K’s portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today’s most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment.</p> <p>Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K’s portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K,&nbsp; renowned BioShock®️, Borderlands®️, Mafia, Sid Meier’s Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K</p> <p>At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don’t meet every requirement for the role.&nbsp; If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply!</p> <p><strong>What We Need</strong></p> <p>The DataOps Engineer is responsible for the operationalization, automation, and reliability of 2K’s data ecosystem. This role applies DevOps principles to data engineering, managing CI/CD for data assets, Infrastructure-as-Code (IaC), and advanced data observability. focuses on complex problem-solving, optimizing cross-functional data flows, and ensuring that data infrastructure is scalable, secure, and highly available for global studio stakeholders.</p> <p><strong>What You Will Do</strong></p> <ul> <li><strong>Data Pipeline Operationalization:</strong> Lead the design and maintenance of scalable ETL/ELT pipelines to ingest and transform data from diverse sources into central data warehouses.</li> <li><strong>Automation &amp; CI/CD:</strong> Implement and manage robust CI/CD pipelines specifically for data assets; automate extraction, testing, and deployment processes to increase velocity and reduce manual intervention.</li> <li><strong>Infrastructure-as-Code (IaC):</strong> Utilize tools such as Terraform to manage and version cloud infrastructure, ensuring environment parity across development, staging, and production.</li> <li><strong>Data Observability &amp; Reliability:</strong> Proactively monitor pipeline health and data quality (freshness, volume, and distribution). Design and build automated alerting systems to resolve bottlenecks.</li> <li><strong>Security &amp; Compliance:</strong> Implement and enforce data security measures, including IAM roles, encryption, and access controls, ensuring all pipelines meet GDPR and CCPA compliance.</li> <li><strong>Platform Support &amp; Collaboration:</strong> Partner with Data Scientists and Analysts to facilitate data availability and provide infrastructure support for complex modeling and insights.</li> <li><strong>Process Optimization:</strong> Identify and execute improvements in data engineering workflows, adopting software engineering best practices for stateful data flows.</li> </ul> <p><strong>Who We Think Will Be A Great Fit </strong></p> <ul> <li><strong>Execution &amp; SLA Excellence:</strong> Consistently meets and exceeds <strong>Service Level Agreements (SLAs)</strong> by streamlining data workflows and maintaining high system availability. Translates business requirements into measurable performance targets.</li> <li><strong>Operational Governance:</strong> Implements rigorous <strong>operational standards</strong> and best practices, leveraging <strong>ITIL frameworks</strong>—specifically Incident, Problem, and Change Management—to minimize downtime and ensure predictable system behavior.</li> <li><strong>Global Collaboration &amp; Follow-the-Sun Support:</strong> Experienced in working with <strong>distributed "around-the-sun" teams</strong>, ensuring seamless handovers, consistent documentation, and 24/7 operational continuity across different time zones.</li> <li><strong>Innovation &amp; Adaptability:</strong> Adapts DevOps and DataOps strategies to handle the unique challenges of data statefulness and rapidly evolving cloud-native technologies.</li> <li><strong>Strategic Problem Solving:</strong> Independently diagnoses and resolves complex architectural bottlenecks; moves beyond "quick fixes" to identify root causes and prevent recurring systemic issues.</li> <li><strong>Communication &amp; Stakeholder Management:</strong> Clearly articulates system health, operational risks, and technical requirements to both technical peers and executive leadership, bridging the gap between data science needs and engineering standards</li> </ul> <p><strong>Required Qualifications, Knowledge, and Job-Related Skills</strong></p> <ul> <li><strong>Experience:</strong> 6+ years of professional experience in DataOps, Data Engineering, or DevOps, with a significant focus on large-scale data systems.</li> <li><strong>Technical Proficiency:</strong> Expert-level Python and SQL skills.</li> <li><strong>Orchestration &amp; Transformation:</strong> Hands-on experience with modern orchestration tools (e.g., Apache Airflow, Mage, or Prefect) and transformation layers (e.g., dbt).</li> <li><strong>Cloud &amp; Containers:</strong> Deep experience with AWS (or GCP/Azure) and containerization technologies such as Docker