Role Overview :

We are seeking a seasoned Senior Data Engineer to architect and scale our next-generation data platforms. In this role, you will lead the design and implementation of robust data pipelines, ensuring high availability and performance of our analytical ecosystem.

You will collaborate closely with cross-functional product teams, data scientists, and business stakeholders to transform raw data into actionable insights that drive strategic decision-making. By building scalable data architectures, you will directly influence the efficiency of our business operations and the quality of data-driven products delivered to our global customer base. This position offers the flexibility of a remote work arrangement with occasional collaboration in the Delhi NCR region.

Key Responsibilities :

- Design and maintain high-performance ETL/ELT pipelines to ingest and process large-scale datasets, ensuring data integrity and reliability for downstream analytics.

- Architect scalable data warehousing solutions on Snowflake or BigQuery to support complex business intelligence requirements and high-concurrency reporting.

- Optimize existing data models and query performance to reduce latency and infrastructure costs, directly improving the speed of business insights.

- Partner with data science and engineering teams to integrate Databricks-based workflows, enabling advanced machine learning models and predictive analytics.

- Establish best practices for data governance, security, and documentation to ensure compliance and maintain a clean, accessible data environment for all stakeholders.

Required Skillset :

- Demonstrated expertise in building and managing complex data warehouses using Snowflake or BigQuery, with a deep understanding of cloud-native data architecture.

- Advanced proficiency in SQL for complex data manipulation and Python for developing automated data processing scripts and pipeline orchestration.

- Proven ability to design and implement efficient ETL/ELT processes that handle high-volume data streams with minimal downtime.

- Hands-on experience with Databricks for distributed data processing and collaborative analytics, showing an ability to bridge the gap between engineering and data science.

- Strong communication skills with the ability to translate technical data challenges into clear, actionable insights for non-technical stakeholders.

- Exceptional problem-solving capabilities and a proactive approach to managing tasks in a remote-first environment, ensuring consistent delivery against project milestones.

- A Bachelor's or Master's degree in Computer Science, Information Technology, or a related quantitative field, reflecting a strong foundation in data engineering principles.