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Job Purpose As a Middle Data Engineer, you will contribute as a skilled individual contributor within cross-functional project teams, taking ownership of data pipeline development and implementation while continuously growing your technical expertise and problem-solving capabilities. You will be responsible for designing efficient data workflows, writing clean, maintainable code, participating in code reviews, and collaborating effectively with senior team members to deliver high-quality data solutions. In this role, you will focus on mastering data engineering practices, expanding your technical knowledge across different areas, and contributing to project success through reliable execution and proactive learning in an agile, collaborative environment. Technical Development & Implementation: Design, develop and optimize data processing workflows aligned with project requirements Implement appropriate data storage and access patterns based on use case requirements Facilitate reliable data movement between systems using batch processing, streaming, or hybrid approaches Write clean, maintainable, and well-documented code with appropriate error handling and monitoring Develop and implement testing strategies to ensure data accuracy, completeness, and performance Troubleshoot and resolve data processing issues with guidance from senior team members when needed Contribute to technical documentation that enables knowledge sharing and system understanding Apply appropriate technologies to solve data challenges based on project context and requirements Collaboration & Professional Growth: Collaborate effectively with cross-functional team members including software engineers, product managers, and other colleagues Participate actively in agile development processes including sprint planning, daily standups, and retrospectives Seek guidance and mentorship from senior team members to accelerate learning and professional development Take initiative in expanding technical knowledge through self-directed learning and training opportunities Contribute to team knowledge sharing through documentation, presentations, or informal knowledge transfer Support onboarding and knowledge transfer for new team members when appropriate Build positive working relationships with team members and demonstrate strong teamwork and collaboration skills Data Standards & Best Practices: Follow established data governance policies and quality assurance procedures for consistent delivery standards Implement data quality monitoring and validation processes for processed data Apply security best practices and data privacy considerations in all engineering work Contribute to continuous improvement initiatives by providing feedback on data processes and suggesting enhancements Maintain awareness of technical debt in data systems and communicate potential issues to senior team members Support data release management activities and participate in deployment processes under guidance Learn and apply industry best practices for data engineering excellence Project Support & Execution: Execute assigned data engineering tasks within established timelines and quality expectations Provide accurate estimates for development work and communicate any risks or blockers proactively Support project planning by contributing technical input on data requirements and architecture considerations Collaborate with team members to resolve technical dependencies and coordinate development efforts Participate in client demonstrations and technical discussions when appropriate and under guidance Contribute to project documentation and ensure clear communication of data engineering decisions Support post-deployment monitoring of data pipelines and resolution of data quality issues Business Adaptability & Professional Growth: Demonstrate Continuous Learning: Actively pursue technical skill development, seek feedback from senior colleagues, and adapt to new technologies and methodologies Drive Ada