Senior Data Engineer (India)

Overview

As a Senior Data Engineer, you will design and build systems that make high-quality data available across the company. You will turn ambiguous business and product questions into durable data models, reliable pipelines, and actionable information.

What you'll do

• Design, build, test, deploy, and maintain scalable cloud-based data pipelines that ingest and transform data from product, operational, and third-party systems.
• Own data-pipeline architecture, including orchestration, monitoring, reliability, performance, and data quality.
• Develop workflows, transformations, and data models that transform raw data into useful, trusted, and actionable information.
• Improve data quality through validation, observability, monitoring, and clear ownership of critical datasets.
• Help manage and improve the existing data stack, including PostgreSQL and Redshift databases, Airflow for orchestration, and Terraform for infrastructure management.
• Help strengthen data literacy across technical and non-technical teams through clear communication and thoughtful partnership.

What you'll need

• 5+ years of experience in data engineering, software engineering, machine learning, or related technical roles.
• Strong experience building, operating, and improving production data pipelines.
• Expertise with relational and columnar databases, including advanced SQL and dimensional data modeling principles such as fact and dimension tables.
• Proficiency with Python, Docker, and workflow-orchestration frameworks such as Apache Airflow.
• Hands-on experience with AWS or comparable cloud platforms.
• Strong grounding in software-engineering practices, including version control, code review, testing, observability, and documentation.
• Excellent written and verbal English communication skills, including the ability to collaborate effectively with globally distributed teams.

Details

• Remote position available only to candidates residing in Bengaluru (formerly known as Bangalore), India.
• The schedule must overlap with U.S. business hours.
• The team operates 100% remotely.