Data Engineer Lead (Data Analytics, Data Warehouse & Big Data)We are seeking a highly skilled Data Engineer Lead to architect, design, and deliver enterprise-scale data solutions across Data Analytics, Data Warehousing, Data Lake, and Big Data environments. This role will lead technical delivery while also guiding a team of engineers in building scalable, high-performance data platforms.
Key Responsibilities- Lead the architecture, design, and implementation of complex data solutions across Data Analytics, Data Warehouse, Data Lake, and Big Data platforms
- Design and govern end-to-end data models (Conceptual, Logical, and Physical) ensuring scalability, performance, and data integrity
- Mentor and guide a team of data engineers, ensuring adherence to coding standards and engineering best practices
- Translate business requirements into technical designs and long-term data architecture roadmaps
- Oversee end-to-end project delivery, including planning, execution, resource management, timelines, and deliverables
- Define and enforce data governance frameworks, data modeling standards, and development best practices
- Act as the escalation point for critical technical issues and client-facing discussions
- Drive innovation, R&D, and upskilling initiatives to keep the team aligned with emerging data engineering technologies
Requirements- Bachelor’s Degree or Diploma in Computer Science, Information Technology, or related field
- 7–8+ years of experience in Data Engineering / Data Analytics / Data Warehouse / Big Data
- At least 2 years of technical leadership or team management experience
- Strong expertise in Data Modeling techniques (Dimensional Modeling/Kimball, Star & Snowflake Schemas, Data Vault, 3NF)
- Expert-level SQL and Python skills
- Good proficiency in Java or Scala is highly preferred
- Proven experience delivering enterprise-scale data platforms and architectures
- Strong experience in performance tuning and optimizing data models for database systems
- Solid understanding of ETL/ELT pipelines and workflows
- Experience with cloud data platforms such as Snowflake, AWS, Azure, or Google Cloud
- Familiarity with Linux/Unix environments and containerization (Docker/Kubernetes) is an advantage
- Experience in Data Governance, Data Quality, or Master Data Management is a plus
- Strong leadership skills with ability to manage teams, delegate tasks, and mentor engineers
- Excellent communication skills with ability to engage stakeholders and senior leadership