In this role, you get to:

• Lead the daily work the DataOps team and manage team backlog: Development, support, maintenance, and automation. If required, ability and willingness to step into individual contributor role and support Data Engineers and Cloud Engineers in their operational tasks.
• Manage expectations, anticipate, and resolve operational risks. Remove barriers and blockers, resolve issues, and solve problems. Provide other ad hoc support where needed. Empower and enable the team to deliver and meet goals.  Makes sure operational priorities are clear.
• Establish and improve Data/DevOps processes and ways of working, and constantly nurture the appetite for automation, learning and continuous improvement of the operations. Build comprehensive & efficient production readiness and enterprise-wide scalability. Have a service-oriented mindset, open and eager to explore the operations end-to-end accountability aligning to business value chains, aim to provide end-to-end service excellence for our business and stakeholders.
• Ensure end-to-end operations alignment for all backlog items and propose and/or create stories that help us deliver operations. Proposes epics or even epic sets to Product Owner based on the understanding of the operations and user needs. Participates in quarterly planning and plan work based on the targets and available information.
• Builds strong relationships with development, operations teams and other stakeholders. Operate with Product Owners, Technical Leads, Execution Leads, DevOps teams, Enterprise Architects, and other relevant stakeholders to oversee and track the operation execution following common IT processes and operating model.
• Lead production crisis analysis and major incidents in own area, supported by service integration function.

To succeed in this role, following professional experience will play a key role:

• Master’s degree in engineering, computer science, management information systems, or a related field.
• A demonstrable background of designing Data/DevOps frameworks, data automations and make them run successfully while continuously improving them. Ability to develop Data/DevOps standards for the Data Engineers, Data Scientists and other data professionals.
• Professional experience of DevOps methods, e.g. automated testing techniques, CI/CD and experience of orchestration tools to author, schedule and monitor data workflows.
• Inbuilt cybersecurity awareness.
• Hands on data engineering experience in developing data pipelines and working with enterprise data infrastructure addressing data across the company in all business process areas.
• Tech stack:  AWS, Gitlab, Databricks for ETL, Airflow, Python, Scala, and DBT for developing ETL, jobs, AWS CDK, Terraform for IaC, Collibra.
• Coding proficiency with multiple languages Python, Scala and DBT.
• Practical experience in working with enterprise data landscapes and data structures: Structural data, non-structural data, metadata, master data, transactional data, batch/NRT, data privacy and compliancy regulations.
• Passion to utilize agile methodologies and tools (Jira, Confluence, draw.io) and continuously improve ways of working.
• Working proficiency in core service management process execution: Incident management, service request, problem management, change management, knowledge management, CMDB.
• Strong experience in working in international environment with stakeholders distributed globally. Experience and capability working in matrix organizations, involving multiple teams from different organization, or reporting lines working in a tribe/hub team, proactively driving things forward. Ability to forge strong relationships and work well with individuals responsible for data across the organization.
• Proficiency in written and spoken English.