Senior Data Engineer

The Role

The Senior Data Engineer serves as a technical authority and subject matter expert responsible for designing, building, and optimizing advanced cloud data lakehouse architectures and enterprise data models. This role combines deep hands-on technical expertise with cross-functional alignment, strategic roadmap prioritization. In addition to driving internal architectural excellence and long-term operational mechanisms, the role owns key customer onboarding initiatives end-to-end and involves traveling to client sites at pivotal project milestones to ensure technical and business success.

What you’ll do (Main responsibilities)

Completing Data Modeling Activities: Be a Subject matter expert.

• Lead data modeling activities, including conceptual, logical, and physical data modeling, to ensure data structures align with business requirements and analytical use-cases.
• Collaborate with cross-functional teams to understand data needs and translate them into effective data models that support data insights and analytics.
• Manages extremely complex projects with unique requirements.

Design State-of-the-Art Cloud-Based Data Lake-house Solutions:

• Conceptualisation, Design and implementation of advanced, cloud-based data lake-house solutions that cater to a wide range of analytical use-cases.
• Consolidate and Optimize Cloud Data Infrastructure:
• Identify opportunities for performance optimization, cost reduction, and resource utilization improvements within the cloud environment.
• Implement process changes according to these opportunities.

Teaching and Sharing Culture:

• Excels at coaching others and leading on the fundamental concepts, practices, and procedures of data engineering.
• Act as a mentor and is a subject matter expert, sharing skills, knowledge, and expertise with earlier in career members of the data engineering team.
• Provide feedback to mentees on their progress, manage and monitor their work and development together with the line manager.
• Foster a culture of collaboration and continuous learning by organizing training sessions, workshops, and knowledge-sharing sessions.

Drive Effective Roadmap Prioritization:

• Collaborate with stakeholders to drive effective roadmap prioritization aligned with company-wide goals and objectives.

Profile and skills:

Technical Skills:

• Deep Understanding and demonstrated expertise in Data Modeling and Data Lake-house Concepts Deep knowledge of fundamental concepts of data modeling, including relational databases, dimensional modeling, and data lake-house architectures. Understanding of how data is structured, organized, and accessed within data lakes and data warehouses
• Becoming a Subject Matter Expert SQL and Python:
• Expertise in SQL for data manipulation, querying, and analysis. Proven programming skills in Python for building data pipelines, performing data transformations, and implementing automation tasks.
• Structured and Analytical Thinking: Structured and analytical approach to problem-solving, with the ability to make sense of complex information and data sets. Strong attention to detail and a methodical approach to data analysis and data engineering tasks.
• Interest in Learning and Growth Mindset: Demonstrated interest in learning and a strong desire to expand knowledge in the field of data engineering. Eagerness to explore new technologies, methodologies, and best practices to enhance data engineering skills and capabilities.
• Collaboration and Knowledge Share: Shares skills, knowledge and expertise across the team
• Initiative and Adaptability: Proactive self-starter with the capacity to engage in multiple initiatives concurrently. Adaptable to changing project requirements and able to anticipate and address potential issues promptly. Enable the One Team + Team Builder approach.
• Curiosity: Keen interest in Everseen's technology solutions, comfortable discussing them at a high level, and staying updated with the latest developments. Constantly suggests and drives ways to improve processes.
• Ownership and Accountability: Demonstrates initiative, drive, and self-motivation in taking full ownership of projects, ensuring accountability for project outcomes, and fostering a no-blame culture conducive to continuous improvement."