Chief Data Innovation Officer

Job Description:

We are seeking a highly skilled and experienced Data Architect to lead our data engineering efforts. The ideal candidate will have a strong background in designing and implementing scalable, high-performance data platforms and applications.

Responsibilities:

• Design and implement enterprise-scale data platforms and applications that include data analysis, data ingestion, storage, data transformation (data pipelines), and analytics.
• Evaluate new trends and features in data platforms and build rapid prototypes.
• Build data solution architectures and frameworks to accelerate the data engineering process.
• Improve reusability, reduce development time, and cost of data management and governance by building frameworks.
• Integrate AI into data engineering practices to bring efficiency through automation.
• Build best practices in data platforms capability and ensure their adoption across product teams.
• Build and nurture strong relationships with stakeholders, emphasizing value-focused engagement and partnership to align data initiatives with broader business goals.
• Lead and motivate a high-performing data platforms team to deliver exceptional results.
• Provide expert guidance and mentorship to the data engineering team, fostering a culture of innovation and best practices.
• Collaborate with counterparts in US and EU and work with business functions, functional IT teams, and others to understand their data needs and ensure solutions meet requirements.
• Engage with business stakeholders to understand their needs and priorities, ensuring data and analytics solutions built deliver real value and meet business objectives.
• Drive adoption of the data and analytics platforms and solutions by partnering with business stakeholders and functional IT teams in rolling out change management, trainings, communications, etc.
• Talent Growth & People Leadership: Lead, mentor, and manage a high-performing team of engineers, fostering an environment that encourages learning, collaboration, and innovation. Focus on nurturing future leaders and providing growth opportunities through coaching, training, and mentorship.
• Recruitment & Team Expansion: Develop a comprehensive talent strategy that includes recruitment, retention, onboarding, and career development and build a diverse and inclusive team that drives innovation, aligns with company culture and values, and delivers business priorities.
• Organizational Leadership: Work closely with senior leaders within the function and across the company site to align engineering goals with broader organizational objectives and demonstrate leadership by contributing to strategic discussions.

Requirements:

• 12 to 17 years with computer science and engineering preferred, other Engineering fields will be considered.
• 10+ years of experience in building Data Platforms, Data Engineering, working in COE development or product building.
• 5+ years of Hands-on experience working with Big Data Platforms & Solutions using AWS and Databricks.
• 5+ years of experience in leading enterprise-scale data engineering solution development.
• Experience building enterprise-scale data lake, data fabric solutions on cloud leveraging modern approaches like Data Mesh.
• Demonstrated proficiency in leveraging cloud platforms (AWS, Azure, GCP) for data engineering solutions. Strong understanding of cloud architecture principles and cost optimization strategies.
• Hands-on experience using Databricks, PySpark, Python, SQL.
• Proven ability to lead and develop high-performing data engineering teams.
• Strong problem-solving, analytical, and critical thinking skills to address complex data challenges.

Preferred Qualifications:

• Experience in Integrating AI with Data Platforms & Engineering and building AI-ready data platforms.
• Prior experience in data modeling especially star-schema modeling concepts.
• Familiarity with ontologies, information modeling, and graph databases.
• Experience working with agile development methodologies such as Scaled Agile.
• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops.

Soft Skills:

• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills.
• Ability to work effectively with global, virtual teams.
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.
• Strong presentation and public speaking skills.