Data Engineer

Articore is a global ecommerce / marketplace company that owns Redbubble and TeePublic — platforms that enable independent artists and creators worldwide to sell their designs on products like apparel, accessories, and home décor. It’s a strong opportunity to work on high-scale engineering problems, global product ecosystems, and creator-focused commerce platforms with an international team.They are now expanding engineering capabilities in Gurugram India, making it an exciting opportunity to work on global consumer products from India

The Senior Data Engineer is responsible for building, maintaining, and scaling the data pipelines that power our global marketplace. This role ensures the reliability of our data ecosystem—specifically within GCP, BigQuery, Snowflake, Airflow, and DBT—by providing critical operational oversight during the India business day. By owning the end-to-end health of our data flows and providing technical support to downstream teams, this role enables the company to make data-driven decisions with confidence.

Core Responsibilities

• Manage and optimize production data pipelines to ensure the timely delivery of high-quality data to our data warehouse.
• Maintain and evolve our transformation models using DBT, ensuring that data is structured for both performance and ease of use by analysts.
• Implement and monitor Service Level Objectives (SLOs) and observability alerts in Datadog to proactively detect and resolve pipeline failures.
• Develop and refine workflow orchestration in Airflow, focusing on reducing technical debt and improving the speed of data processing.
• Collaborate across time zones with the Melbourne and New York teams to provide "follow-the-sun" support, ensuring global system stability.
• Lead data modeling efforts, transforming raw application and third-party data into well-structured, warehouse-ready assets (using Kimball or "one-big-table" paradigms) to solve specific business challenges.

• Mentor and elevate the engineering team through rigorous code reviews, documentation standards, and the adoption of modern transformation tools like dbt and SQLMesh
• Execute migration projects that move legacy data structures into our modern cloud architecture, improving long-term system maintainability.
• Implement and maintain systems for data governance, focusing on automated testing, data quality, consistency, and privacy compliance across all global pipelines
• 5+ years of experience building and maintaining production-grade data pipelines in a cloud-native environment (GCP preferred, or AWS).
• Technical Mastery: Deep proficiency in Python and SQL, with a strong background in data modeling and API integration.
• Modern Data Stack Expertise: Hands-on experience with ₹Query/Snowflake, DBT, and Airflow (or similar orchestration tools like Dagster or Prefect).
• Distributed Systems Knowledge: Understanding of how to process large-scale datasets efficiently using tools like Spark or BigQuery.
• Collaborative Communication: Ability to work effectively in a distributed team, clearly documenting technical changes and participating in global handover processes.
• Operational Excellence: You have a reliability-first mindset, taking pride in high uptime and the accuracy of the data you deliver.
• Empathetic Engineering: You view data as a product and strive to make it accessible and understandable for your stakeholders across the business.
• Adaptable Problem-Solver: You thrive in a fast-paced environment and are comfortable shifting between deep-focus development and urgent troubleshooting.
• Continuous Learner: You stay curious about emerging data technologies and are always looking for ways to automate manual processes.
• Strategic Ownership: You have the ability to work independently, lead complex projects, and work through ambiguity to build repeatable engineering patterns