Principal Data Architect - 25247

Why YOU want this position

At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world. 

We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy.

The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.

Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.

Enverus has a dynamic hub for developing software in Brno, Czech Republic, and you can learn more about our team, company culture, and benefits https://www.enverus.com/careers/brno/" target="_blank">here.   

The Team:

The Corporate Data & Analytics Team is seeking a Principal Data Architect who will lead the design and implementation of enterprise data architecture solutions. As the principal data architect, you will leverage your extensive expertise in data architecture, integration, and analytics to deliver solutions that align with business and stakeholder outcomes. This role requires a blend of technical expertise, strategy, and leadership skills to ensure solutions are aligned with business objectives while planning for future needs of the organization.

Performance Objectives

• Leading the design and implementation of scalable, secure, and efficient data solutions that enable the seamless data flow between source systems, applications, and platforms. 

• Developing team-wide strategies for data integration, transformation, and retrieval across structured and unstructured data systems.

• Driving architecture reviews to identify gaps and recommend design improvements.

• Guiding data lifecycle management, from data collection, processing, storage, archival, and disposal.

• Collaborating with business leaders, security, data engineering, business intelligence, analytics, and other teams to ensure data architecture and solutions support business needs.

• Developing and maintaining architecture design documents and roadmaps design patterns.

• Leading current and new platform and tools analysis based on qualitative and quantitative evaluations, proof of concepts, and testing.

• Ensuring data architecture and solutions meet security, privacy, and corporate regulatory requirements.

Competitive Candidate Profile

• 10+ years of experience in designing, developing, and managing large-scale data architectures, including data lakes, data warehouses, and cloud environments (AWS, DBT)

• 8+ years of experience in cloud native-data architectures, data integration, API-based data integration, ELT/ETL, batch, and real-time data processing. DBT expertise strongly preferred.

• 8+ years of experience in Python and modern data platforms.

• 8+ years of experience in SQL/NoSQL databases, cloud databases, and data streaming technologies.

• 6+ years of experience in data platforms, Snowflake strongly preferred.

• Expertise in cloud design and architecture in AWS with a focus on Lambda and S3 to deliver large-scale distributed solutions.

• Strong business acumen with the ability to align data/information architecture strategies with business objectives.

• In-depth knowledge of data management, data governance frameworks, data cataloging, and master data management.

• Strong problem-solving abilities in complex data and analytics challenges.

• Excellent communication skills, engaging both technical and non-technical stakeholders

• Strong Knowledge in BI Tools, Power BI, etc.

Our Technology Stack: 

Snowflake, dbt, SQL, Python, Power BI