Data Engineer

Role Overview

We are seeking a Data Engineer to design, build, and maintain reliable data pipelines, models, and data products that support business analytics and applications. You will transform raw data into high-quality, well-structured, and trusted datasets, ensuring data accuracy, consistency, and reliability.

Working closely with platform, analytics, product, and engineering teams, you will contribute to scalable data solutions while strengthening your technical expertise in a fast-paced, global environment.

Key Responsibilities

• Data Pipeline Development: Design, develop, and maintain batch and streaming data pipelines and models to support analytics and business applications.
• Data Processing & Management: Implement data cleansing, standardization, incremental processing, reconciliation, and dataset publishing to ensure reliable data delivery.
• Data Quality & Testing: Develop automated tests and data quality checks, monitoring data timeliness, completeness, accuracy, and consistency.
• Cross-Functional Collaboration: Work with business stakeholders, analytics, product, and engineering teams to understand data requirements and establish clear data definitions.
• Production Support & Optimization: Participate in code reviews, deployments, production troubleshooting, data backfills, and ongoing pipeline improvements.
• Documentation & Governance: Maintain technical documentation, data contracts, and operational runbooks to support sustainable data operations.

Requirements

• Bachelor's degree or above in Computer Science, Data Science, or a related field, or equivalent practical experience.
• At least 3 years of experience in data engineering, analytics engineering, data warehousing, or a related discipline.
• Strong SQL skills and hands-on experience developing and maintaining data pipelines using Python.
• Solid understanding of data warehouse modelling, incremental processing, workflow orchestration, and data quality management.
• Strong analytical and problem-solving skills, with a focus on code quality, testing, and technical documentation.

Nice-to-Have

Experience with Databricks, Apache Spark, dbt, Airflow, or similar data engineering technologies.
Experience working with commerce, advertising, order, user, or consumer datasets.
Familiarity with cloud-based data platforms and distributed engineering teams.

Regret to inform that only shortlisted candidates will be notified.
EA Registration Number: R1878287
Business Registration Number: 201735941W.