Data Engineer - Global Team

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer - Global Team based in India.

This role offers the opportunity to join a high-impact data engineering team supporting large-scale analytics and data-driven products.
You will design, build, and optimize reliable data pipelines that transform complex datasets into valuable business insights.
The position combines technical depth, problem-solving, and collaboration with global teams in a fast-moving environment.
You will work with modern data technologies, including Spark, PySpark, SQL, Databricks, and AI-ready data solutions.
This is an opportunity to contribute to the foundation of scalable data infrastructure while continuously developing your technical expertise.
You will play a key role in improving data quality, efficiency, and accessibility for teams relying on advanced analytics.

• Build, maintain, and optimize end-to-end data pipelines that support critical analytical products and business operations.
• Develop scalable data processing solutions using technologies such as PySpark, Spark, SQL, and Databricks.
• Design and implement best practices for data modeling, pipeline architecture, reliability, and performance optimization.
• Create AI-ready analytical datasets with the appropriate structure, metadata, documentation, and business context to support AI applications and advanced analytics.
• Troubleshoot and resolve complex data pipeline challenges while improving system efficiency and scalability.
• Collaborate with cross-functional stakeholders to understand business requirements and incorporate relevant logic into centralized data workflows.
• Support the continuous improvement of internal data engineering tools, frameworks, and processes.
• Work closely with engineering leadership and global teams to deliver reliable, high-quality data solutions.
• Learn and apply emerging technologies across data engineering, artificial intelligence, ETL, and analytics ecosystems.
• Contribute to establishing technical standards and practices as the data engineering function continues to grow.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, STEM, or a related technical discipline.
• 4+ years of experience working as a Data Engineer or in a similar technical role involving data systems and pipelines.
• Strong understanding of data engineering concepts, including data processing, transformation, modeling, and pipeline development.
• Hands-on experience working with large-scale datasets using PySpark, Spark, SQL, Delta Lake, and Databricks.
• Experience designing, developing, and maintaining reliable data pipelines in production environments.
• Ability to understand business requirements and translate them into effective data solutions aligned with organizational goals.
• Strong analytical and problem-solving skills with the ability to investigate and resolve complex technical challenges.
• Comfortable learning new technologies and adapting to evolving data platforms and tools.
• Self-motivated approach with the ability to work independently while collaborating effectively with global teams.
• Excellent verbal and written communication skills.
• Experience with additional data technologies such as Airflow, dbt, Snowflake, or similar platforms is a plus.
• Ability to overlap with US working hours during onboarding and participate in occasional meetings with international teams after the training period.

Benefits:

• Remote work opportunity based in India.
• Competitive salary package with comprehensive benefits.
• Flexible working approach with standard IST hours after onboarding, including limited overlap with global teams when required.
• Vacation time, parental leave, team events, and employee-focused programs.
• Learning and development support, including opportunities for continuous technical growth.
• High-impact role with ownership over meaningful data engineering projects.
• Opportunity to work with modern technologies across data engineering, AI, analytics, and cloud ecosystems.
• Collaborative global environment focused on innovation, trust, and professional development.
• Career growth opportunities based on impact, skills development, and contributions rather than tenure.