Senior Data Engineer (Hybrid, AU hours) | Cubao

About the position

About the job: Senior Data Engineer (Hybrid) | Cubao Schedule: AU Hours Work Setup: 3x Onsite weekly (Gateway, Cubao) Senior Data Engineer with extensive hands-on experience in Data Architecture and Engineering to serve as a technical contributor within our team. As a senior data engineer, you will be responsible for designing, building, and deploying cutting-edge data solutions while contributing to establishing our data practice. Responsibilities: Contribute to technical engagements and proactively identify opportunities to expand CI&T's business with clients. Collaborate on multiple projects across various domains, providing diverse subject matter expertise. Participate in technical design and architecture discussions to ensure robust solutions. Ensure adherence to security and performance best practices in all solutions. Create and maintain technical documentation required by clients. Communicate effectively with customer team members to ensure alignment and clarity of technical solutions. Understand client requirements and develop viable technical solutions by selecting appropriate frameworks. Guarantee a stable and productive development environment for all team members. Requirements: 6+ years of experience in the software development area Proven expertise in data warehousing and data analytics projects, encompassing data acquisition, transformation, and data science initiatives. Exposure to modern data file formats such as Delta Tables, Apache Iceberg, and Parquet. Proficiency in Python, Spark, DBT, and other data transformation tools and frameworks. Expertise in data modelling, with familiarity in conceptual, logical, and physical data models, following methodologies like Data Vault 2.0 and dimensional modelling. Experience with cloud data services such as Microsoft Intelligent Data Platform, AWS Data Services, or Google Cloud Data Analytics. Minimum of 3 years experience with Snowflake Hands-on experience with cloud data platforms like Databricks and/or Snowflake; certifications. Skilled in data pipeline orchestration tools, including Azure Data Factory, AWS Glue, Apache Airflow, or Prefect. Experience with CI/CD and MLOps pipelines to streamline development and deployment processes. Proficient in Infrastructure as Code (IaC) for efficient infrastructure management. Expertise in data migration, performance tuning, and optimization of databases and SQL queries. Understanding of data governance and data management concepts. Understanding design patterns, clean architecture, and clean coding principles. Familiarity with unit, integration, and E2E testing.

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