Data Engineering Lead - Python/Scala

Data Engineering Lead Experience : 7 to 10 years Location : Hyderabad Must have : - Experience in data engineering with hands-on expertise in data pipeline development, architecture, and system optimization. - Experience in programming languages such as Python, or Scala - Experience in Data Warehouses (e.g., Snowflake, Redshift) - Experience in ETL/ELT tools such as Matillion, dbt, Striim - Experience in end-to-end implementation of projects with multiple transformation layers. - Team handling (4 to 5 members) Job Description : We are looking for an accomplished and dynamic Data Engineering Lead to join our team and drive the design, development, and delivery of cutting-edge data solutions. This role requires a balance of strong technical expertise, strategic leadership, and a consulting mindset. As the Lead Data Engineer, you will oversee the design and development of robust data pipelines and systems, manage and mentor a team of 5 to 7 engineers, and play a critical role in architecting innovative solutions tailored to client needs. You will lead by example, fostering a culture of accountability, ownership, and continuous improvement while delivering impactful, scalable data solutions in a fast-paced, consulting environment. Key Responsibilities : 1. Data Solution Design and Development : - Architect, design, and implement end-to-end data pipelines and systems that handle largescale, complex datasets. - Ensure optimal system architecture for performance, scalability, and reliability. - Evaluate and integrate new technologies to enhance existing solutions. - Implement best practices in ETL/ELT processes, data integration, and data warehousing. 2. Project Leadership and Delivery : - Lead technical project execution, ensuring timelines and deliverables are met with high quality. - Collaborate with cross-functional teams to align business goals with technical solutions. - Act as the primary point of contact for clients, translating business requirements into actionable technical strategies. 3. Team Leadership and Development : - Manage, mentor, and grow a team of 5 to 7 data engineers. - Conduct code reviews, validations, and provide feedback to ensure adherence to technical standards. - Provide technical guidance and foster an environment of continuous learning, innovation, and collaboration. 4. Optimization and Performance Tuning : - Analyze and optimize existing data workflows for performance and cost-efficiency. - Troubleshoot and resolve complex technical issues within data systems. 5. Adaptability and Innovation : - Embrace a consulting mindset with the ability to quickly learn and adopt new tools, technologies, and frameworks. - Identify opportunities for innovation and implement cutting-edge technologies in data engineering. - Exhibit a "figure it out" attitude, taking ownership and accountability for challenges and solutions. 6. Client Collaboration : - Engage with stakeholders to understand requirements and ensure alignment throughout the project lifecycle. - Present technical concepts and designs to both technical and non-technical audiences. - Communicate effectively with stakeholders to ensure alignment on project goals, timelines, and deliverables. 7. Learning and Adaptability : - Stay updated with emerging data technologies, frameworks, and tools. - Actively explore and integrate new technologies to improve existing workflows and solutions. 8. Internal Initiatives and Eminence Building : - Drive internal initiatives to improve processes, frameworks, and methodologies. - Contribute to the organization's eminence by developing thought leadership, sharing best practices, and participating in knowledge-sharing activities. (ref:hirist.tech)

Location: hyderabad, IN

Posted Date: 3/26/2025