Senior D ata Engineer Competencies
1. Cognitive Ability (30%)
- Demonstrates strong deductive reasoning and structured problem-solving, breaking down complex and ambiguous challenges into clear hypotheses and logical conclusions.
- Balances short-term tactical needs with long-term scalability by evaluating tradeoffs in real time.
- Integrates diverse data and business inputs into coherent models that enable better decisions.
- Assesses alternative architectures, tools, or approaches and selects the path that maximizes enterprise value.
2. Execution Orientation (25%)
Translates complex requirements into production-ready data pipelines, ensuring solutions move from concept to reality.Maintains accountability for delivery in fast-paced, M&A-driven environments, persisting through ambiguity and shifting priorities.3. Attention to Details (20%)
Applies precision in relational and non-relational database design, ensuring schemas are optimized for both reliability and performance.Designs and adapts ETL / ELT pipelines with a disciplined approach, selecting and applying modern tools (e.g., Airflow, dbt, Python) while upholding exacting quality standards.Establishes rigorous validation and monitoring practices to safeguard accuracy, consistency, and trustworthiness across complex data flows.4. System Thinking (15%)
Recognizes interdependencies across ERP, finance, and operational systems, integrating them into unified models that enable scale and long-term resilience.Envisions and designs analytics-ready data architectures that serve diverse use cases, from real-time operations to enterprise reporting.Applies governance and metadata practices not as compliance exercises, but as mechanisms to keep systems coherent, secure, and adaptable as the business evolves.5. Empathy & Collaboration (10%)
Builds alignment across engineering, finance, and operations by translating technical concepts into clear, accessible language.Guides teams and vendors with a collaborative approach, creating trust and accountability while maintaining technical rigor.Balances advocacy for best-practice architecture with empathy for business constraints, enabling pragmatic solutions that teams can adopt and sustain.Establishes and enforces validation, quality, and monitoring standards so that systems remain dependable at scale.