Data Engineering Lead - Python/Scala (7-10 yrs)

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.