Yêu cầu công việc
Experience and Responsibilities:
Skilled in data analysis and able to interpret complex data sets and derive actionable insights.
Assist the team leader in project management and provide business- as- usual (BAU) support services.
Define and standardize data assets to ensure high- quality data delivery while supporting the design and development of scalable data architectures and integration solutions.
Able to understand cloud- based infrastructure and have experience working with data visualization tools such as Tableau, Looker Studio, and Power BI.
Collaborate with cross- functional teams, including Data Science and Data Product teams, to define data models, architecture, and transformations using tools like DBT (SQL/Jinja).
A minimum of 4 years SDE experience specifically in a data engineering role, including working with large- scale data platforms.
Bachelor’s or master&039;s in Data science, Data Engineering, Computer Science or a related field.
Design, develop, and maintain robust data pipelines to support analytics and business needs by ingesting and processing data from various sources into the cloud platform.
A basic understanding of Google Tag Manager and Google Analytics setup, testing, and validation is a plus.
Experience with big data tools like Databricks and Spark and cloud- based platforms like BigQuery for large- scale data analytics.
Ensure data quality, reliability, and security by supporting Data Governance processes.
Proficient in Python- based data engineering (Mage) and SQL (MySQL, PostgreSQL, NoSQL).
Knowledge of ETL/ELT best practices, data warehousing concepts, and experience with data modeling techniques.
Qualification and Personal Characteristics:
Self- initiative, proactive, and forward- thinking, focusing on continuously improving data platforms and processes.
Excellent communication and teamwork skills, with the ability to work collaboratively with user departments and vendors.
Strong customer service mindset, with the ability to train and mentor team members, identifying skills and gaps.
Strong problem- solving and analytical skills with attention to detail.
Ability to learn new technologies quickly and innovate within the data space.
