[Job- 29791] Senior Data Engineer [Databricks required] (Hybrid 3x/wk)

Senior Data Engineer Job Purpose As a Senior Data Engineer, you will serve as a technical leader and mentor within cross-functional project teams, taking ownership of complex data solutions and architectural decisions within your area of expertise. You will be responsible for designing and implementing high-performance data systems, including data pipelines, storage solutions, and processing frameworks, while mentoring junior and middle-level colleagues and ensuring technical excellence through comprehensive code reviews and testing practices. In this role, you will contribute to data strategy discussions, lead the implementation of critical data workflows, and bridge the gap between technical execution and business objectives. You will also maintain strong client relationships and support pre-sales activities when needed. Required Technical Stack Core Tech Stack: SQL | Python | PySpark | Databricks | AWS SQL – Strong proficiency in writing complex queries, data transformation, optimization, and working with large datasets Python – Strong experience in Python for data engineering, automation, data processing, and pipeline development PySpark – Hands-on experience developing and optimizing distributed data processing workflows using PySpark Databricks – Strong hands-on experience with Databricks for data engineering, data processing, pipeline development, and analytics AWS – Hands-on experience designing, implementing, and supporting cloud-based data solutions using AWS services Key Accountabilities Technical Leadership & Engineering Excellence Lead the design and implementation of features, including complex data processing workflows and pipelines, with high attention to detail and quality standards Design, develop, and optimize scalable data solutions using SQL, Python, PySpark, Databricks, and AWS Contribute to architecture decisions within project scope and provide technical input for broader data strategy discussions Establish and maintain engineering standards, best practices, and comprehensive testing strategies within development teams Conduct thorough code reviews and drive adoption of a strong peer review culture for continuous improvement Lead troubleshooting of complex technical issues and provide innovative solutions to challenging data engineering problems Drive performance optimization initiatives for data systems and ensure scalability and reliability in technical implementations Evaluate data processing frameworks, cloud technologies, and emerging tools for potential adoption within projects Lead proof-of-concept development and technical risk assessments for new data initiatives Ensure data solutions are secure, maintainable, reliable, and aligned with business and technical requirements Team Development & Mentorship Mentor and develop junior and middle-level colleagues across different technical areas and specializations Provide technical guidance, knowledge sharing, and support for the career progression of team members Support technical hiring processes through candidate evaluation, interviewing, and technical assessments Contribute performance evaluation input and provide constructive feedback for team members Develop and deliver technical training sessions to elevate team capabilities and foster a culture of continuous learning Lead by example in adopting engineering best practices, including test-driven development and automated testing approaches Support team collaboration and knowledge transfer across different technical domains and projects Share expertise in SQL, Python, PySpark, Databricks, AWS, and other relevant data engineering technologies Project Execution & Delivery Take ownership of complex technical tasks and ensure timely, high-quality delivery within project timelines Design and implement reliable and scalable data pipelines and processing workflows Provide accurate technical estimations and planning input for development tasks and project milestones Coordinate technical dependencies and c