Data Engineer - Social, Healthcare and Public Entities Tech

As a member of the team at the company, you will be working on driving lasting impact and building long-term capabilities with clients in a high performance/high reward culture. You will have the resilience to try new approaches and the determination to pick yourself up when facing challenges. Your development will be supported by resources, mentorship, and opportunities to become a stronger leader. Your colleagues will deeply invest in your growth while delivering exceptional results for clients. You will receive apprenticeship, coaching, and exposure that accelerate your professional development. Key Responsibilities: - Support the development, maintenance, and enhancement of data pipelines and workflows for analytics and AI-driven solutions in social, healthcare, and public sector domains. - Collaborate with SHaPE analytics teams in various technology hubs to build and maintain reliable, scalable, and efficient data pipelines and ETL workflows. - Use tools like Python, SQL, and distributed data platforms to work with structured and unstructured data, contributing to the development of data models, transformations, and data quality checks. - Test, debug, and monitor data workflows to ensure smooth and reliable data delivery, participate in code reviews, follow engineering best practices, and document data processes for maintainability and knowledge sharing. - Collaborate with data engineers, data scientists, and consulting teams to deliver high-quality data solutions supporting analytics and AI-driven insights. Qualifications Required: - Bachelors degree in Computer Science, Engineering, or a related field. - 2+ years of experience in data engineering, software engineering, or a related role. - Proficiency in Python and SQL with a basic understanding of data structures and algorithms. - Understanding of data processing frameworks, ETL/ELT pipelines, and data warehousing concepts. - Familiarity with Git/version control systems, cloud platforms, and distributed data platforms. - Basic understanding of CI/CD concepts, APIs, and data integration techniques. - Knowledge of statistical data analysis using R is a plus. - Strong problem-solving skills and a willingness to learn in a fast-paced environment. - Interest in AI/ML applications, with exposure to applying data engineering in social, healthcare, or public sector domains. As a member of the team at the company, you will be working on driving lasting impact and building long-term capabilities with clients in a high performance/high reward culture. You will have the resilience to try new approaches and the determination to pick yourself up when facing challenges. Your development will be supported by resources, mentorship, and opportunities to become a stronger leader. Your colleagues will deeply invest in your growth while delivering exceptional results for clients. You will receive apprenticeship, coaching, and exposure that accelerate your professional development. Key Responsibilities: - Support the development, maintenance, and enhancement of data pipelines and workflows for analytics and AI-driven solutions in social, healthcare, and public sector domains. - Collaborate with SHaPE analytics teams in various technology hubs to build and maintain reliable, scalable, and efficient data pipelines and ETL workflows. - Use tools like Python, SQL, and distributed data platforms to work with structured and unstructured data, contributing to the development of data models, transformations, and data quality checks. - Test, debug, and monitor data workflows to ensure smooth and reliable data delivery, participate in code reviews, follow engineering best practices, and document data processes for maintainability and knowledge sharing. - Collaborate with data engineers, data scientists, and consulting teams to deliver high-quality data solutions supporting analytics and AI-driven insights. Qualifications Required: - Bachelors degree in Computer Science, Engineering, or a related field. - 2+ years of experience in data engineering, software engineering, or a related role. - Proficiency in Python and SQL with a basic understanding of data structures and algorithms. - Understanding of data processing frameworks, ETL/ELT pipelines, and data warehousing concepts. - Familiarity with Git/version control systems, cloud platforms, and distributed data platforms. - Basic understanding of CI/CD concepts, APIs, and data integration techniques. - Knowledge of statistical data analysis using R is a plus. - Strong problem-solving skills and a willingness to learn in a fast-paced environment. - Interest in AI/ML applications, with exposure to applying data engineering in social, healthcare, or public sector domains.