Lead Engineer - Data

Experience: - Minimum 10 years of experience in Data Engineering or related roles - At least 2+ years in a Technical Lead (Data) capacity - Note: This is not a management position — 100% hands-on capability required Key Responsibilities - Technically Lead and mentor a team of data engineers , fostering growth, collaboration, and technical excellence across project delivery. - Architect, design, and implement scalable data pipelines and processing systems using modern cloud services (AWS, GCP, Azure). - Establish and enforce data engineering best practices , standards, and governance frameworks. - Collaborate with business stakeholders to understand data needs and deliver actionable, scalable solutions. - Drive the technical vision and roadmap for data infrastructure and platforms. - Optimize data workflows for performance, reliability, and cost efficiency. - Provide technical leadership in data modeling and ETL/ELT design . - Conduct code reviews , ensuring scalable and maintainable solutions. - Support teams and stakeholders with data-related problem-solving. - Communicate technical concepts effectively to technical and non-technical audiences. - Design and lead discovery sessions with clients and internal teams for requirement gathering and architecture alignment. - Automate and orchestrate complex data pipelines , reducing manual effort. - Develop and maintain high-quality documentation of architectures, requirements, and processes. - Support pre-sales engagements , including technical solutioning and proposal development. - Create reusable frameworks and artifacts to accelerate delivery. - Maintain relevant cloud certifications and contribute to thought leadership. Technical Skills & Competencies Programming & Querying Expertise - Proficiency in Python and SQL is essential, with proven experience in developing scalable data solutions. - Strong skills in writing clean, testable, and production-grade code for data transformation and orchestration. - Experience with version control systems like Git and collaborative development practices. - Familiarity with Scala or Java is a plus, particularly for big data processing frameworks. Data Lake & Data Warehouse Expertise - Proven experience in designing and implementing enterprise-grade data lake solutions . - Hands-on experience with Cloud Data Engineering (AWS/GCP) , Databricks , Delta Lake , and lakehouse architectures . - Strong understanding of data warehouse concepts , including star and snowflake schemas . - Expertise in query performance tuning , data partitioning , compression , and storage optimization . - Understanding of data governance, access control , and security frameworks . - Familiarity with medallion architecture or equivalent multi-tier data processing frameworks. - Experience with real-time data streaming technologies such as Apache Kafka or AWS Kinesis . Leadership & Soft Skills - 2+ years of technical leadership experience. - Demonstrated ability to mentor junior engineers and foster team capability growth. - Excellent communication and collaboration skills across cross-functional teams. - Strong problem-solving abilities , business acumen , and analytical thinking. - Ability to manage multiple priorities in dynamic, fast-paced environments. - Customer-focused mindset with strong stakeholder engagement skills. - Experience in Agile methodologies and leading sprint planning and retrospectives. Data Engineering Core Principles - Expertise in data pipeline architectures , data integration patterns, and orchestration tools. - Experience with data validation , testing frameworks , and data quality management. - Knowledge of data privacy , compliance , and security best practices . - Experience in connecting data pipelines to visualization layers for real-time analytics. - Understanding of semantic layer design and self-service data modeling . - Experience in end-to-end or