数据开发主任

About the Role

We are looking for a Junior Data Engineer to join our data platform team. You will work on building and maintaining data pipelines, supporting cloud-based data infrastructure, and ensuring data availability for downstream consumers. This role sits close to the business — you will collaborate directly with data scientists and business analysts to understand data needs, learn domain knowledge, and translate business requirements into technical solutions. This is an excellent opportunity for someone eager to grow both technically and in business understanding.

Responsibilities

• Develop and maintain data pipelines for ingestion, transformation, and delivery across cloud environments
• Support and monitor data platform operations, including participation in 24×7 on-call rotation
• Write and optimize Python and PySpark scripts for data processing at scale
• Create and maintain Linux shell scripts for automation and job scheduling
• Assist with database operations including data extraction, loading, and troubleshooting across Oracle, MySQL, and document databases
• Design and maintain data warehouse structures including fact tables, dimension tables, and SOR implementations
• Work closely with data scientists to prepare and deliver high-quality datasets for analytics and machine learning
• Engage with business stakeholders to understand data requirements, business logic, and domain-specific knowledge
• Investigate and resolve data quality issues and pipeline failures
• Document technical processes and contribute to operational runbooks

Requirements

• Diploma or degree in Computer Science, Information Technology, or related discipline
• 2+ years of experience in data engineering, software development, or related fields
• Basic knowledge of Python programming
• Familiarity with Linux operating systems and command-line operations
• Understanding of relational databases and SQL fundamentals
• Basic understanding of data warehouse concepts (star schema, dimensional modeling, ETL/ELT)
• Strong problem-solving skills and willingness to learn new technologies
• Genuine interest in understanding business operations and translating business needs into data solutions
• Ability to work in a team and communicate effectively with both technical and non-technical stakeholders
• Comfortable with shift work or on-call arrangements for production support
• Strong sense of ownership — takes responsibility for assigned tasks from start to finish, including follow-through on production issues
• Proactive and self-driven, able to identify problems and take initiative without waiting to be told
• Accountable for the quality and reliability of deliverables, with a mindset of "if I built it, I own it"
• Willingness to go the extra mile during critical incidents and take personal responsibility for resolution

Nice to Have

• Experience with Google Cloud Platform (BigQuery, Dataproc, Cloud Storage)
• Experience with AWS services (S3, Lambda, Redshift, EMR)
• Exposure to Apache Spark or PySpark
• Knowledge of shell scripting (Bash)
• Experience with NoSQL or document databases (MongoDB, DynamoDB)
• Familiarity with workflow orchestration tools (Airflow, Cloud Composer)
• Understanding of data warehouse methodologies (Kimball, Inmon, Data Vault)
• Experience collaborating with data science or analytics teams
• Exposure to BI tools or data visualization platforms

What We Offer

• Hands-on experience with multi-cloud data platforms (GCP and AWS)
• Mentorship from senior data engineers
• Opportunity to work on enterprise-scale data pipelines
• Deep exposure to business domains through close collaboration with data scientists and business teams
• Career growth path into senior data engineering, data architecture, or analytics engineering roles