Data Engineering Lead

Data Engineering Lead

Key Responsibilities

• Lead the design and implementation of ESG data, reporting, and analytics solutions across the organization.
• Define technical architecture, data models, and integration frameworks for ESG data platforms.
• Collaborate with business stakeholders, sustainability teams, and technology teams to translate ESG reporting requirements into scalable technical solutions.
• Provide technical leadership to data engineering, analytics, and data science teams throughout the solution lifecycle.
• Drive the development of ESG dashboards, KPIs, scorecards, and performance monitoring frameworks.
• Oversee the ingestion, transformation, validation, and management of ESG datasets, including carbon emissions, sustainability metrics, and regulatory reporting data.
• Establish and enforce ESG data governance, data quality, metadata management, and reporting standards.
• Ensure ESG solutions align with global reporting frameworks and regulatory requirements, including GRI, SASB, TCFD, ISSB, and other emerging standards.
• Review technical designs, code, and implementation approaches to ensure scalability, reliability, and maintainability.
• Lead system integration efforts across internal and external ESG data sources and reporting platforms.
• Support advanced analytics initiatives, including predictive modeling, sustainability insights, and ESG risk analysis.
• Manage technical delivery, project planning, risk management, testing, and production deployments.
• Mentor technical team members and promote best practices in data engineering, analytics, and ESG technology solutions.
• Act as the primary technical advisor for ESG-related initiatives and stakeholder engagements.

Required Skills and Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, Sustainability, Finance, or a related discipline.
• 8+ years of experience in data, analytics, or technology delivery roles, with at least 3 years in a technical leadership capacity.
• Strong understanding of ESG concepts, sustainability reporting frameworks, and regulatory requirements.
• Proven experience designing and delivering enterprise-scale data and analytics solutions.
• Strong expertise in data architecture, data modeling, ETL/ELT processes, and data governance frameworks.
• Hands-on experience with data visualization and analytics platforms such as Power BI or Tableau.
• Proficiency in SQL and working knowledge of Python or R for data analysis and automation.
• Familiarity with cloud-based data platforms and modern data engineering technologies.
• Experience leading cross-functional teams within Agile delivery environments.
• Strong knowledge of data quality, master data management, and reporting controls.
• Excellent stakeholder management, communication, and leadership skills.
• Ability to bridge business objectives with technical implementation and drive successful project outcomes.

Preferred Qualifications

• Experience within financial services, banking, consulting, or sustainability-focused organizations.
• Exposure to ESG data providers, sustainability reporting platforms, or regulatory reporting systems.
• Knowledge of machine learning, predictive analytics, or advanced statistical modeling techniques.
• Relevant certifications in ESG, sustainability reporting, cloud technologies, or data management are advantageous.