Role Overview :

As a Lead Data Engineer, you will spearhead the design and implementation of scalable data architectures that serve as the backbone for our enterprise-level decision-making. You will operate at the intersection of engineering and strategy, collaborating closely with data scientists, product managers, and executive stakeholders to transform complex raw data into actionable business intelligence.

By architecting robust data pipelines and optimizing cloud-native infrastructure, you will directly influence our ability to deliver high-performance analytics, ultimately driving operational efficiency and superior customer experiences across our global product suite. This role is based in Noida/Gurgaon and requires a leader capable of steering technical vision while mentoring high-performing engineering teams.

Key Responsibilities :

- Architect and maintain end-to-end data pipelines to ensure high availability and data integrity for downstream analytics and machine learning applications.

- Lead the migration and optimization of legacy data systems to modern cloud-native environments to improve processing speed and reduce operational costs.

- Collaborate with cross-functional stakeholders to define data governance standards and security protocols that protect sensitive information while ensuring accessibility.

- Mentor junior engineers through code reviews and technical guidance to foster a culture of engineering excellence and continuous improvement.

- Partner with product teams to translate complex business requirements into scalable technical solutions that provide a competitive edge in the market.

Required Skillset :

- Demonstrate mastery in designing distributed systems and large-scale data processing frameworks using technologies such as Spark, Flink, or Kafka to handle petabyte-scale datasets.

- Exhibit deep proficiency in cloud platforms like AWS, Azure, or GCP, specifically in deploying and managing data warehouses and data lakes.

- Possess strong interpersonal skills to effectively communicate complex technical concepts to non-technical stakeholders and influence decision-making at the leadership level.

- Showcase a proven ability to lead and inspire technical teams in a hybrid work environment, balancing hands-on development with strategic oversight.

- Hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, backed by 8 to 12 years of progressive experience in data engineering roles.

- Adapt seamlessly to fast-paced, agile environments, demonstrating a proactive approach to problem-solving and technical debt management.