Data Engineer Analyst - 6 month contract

About the role

The primary purpose of this position is to design, implement and manage Trading and Shipping data infrastructure within the Snowflake platform. He or she will play a crucial role in ensuring data is ingested, processed, transformed and made available for analysis and reporting. This role will work with data analysts and business users to understand data requirements and create scalable data solutions. Given that Ampol has just migrated to data lake in Snowflake, He or she will also be expected to monitor and maintain the existing data pipelines and overall health of Snowflake data infrastructure.

Key responsibilities

1. Data Strategy and Planning: Continuously develop and enhance Ampol data strategy and architecture and roadmap to ensure alignment to business requirements and overall company vision.
2. Data Exploration and Analysis: Explore data to identify patterns, trends and insights. Perform quantitative and qualitative analysis to answer specific business questions and to gain a deeper understanding of data.
3. Data Pipeline Development: Build and maintain data pipelines to move and transform data from various sources into Snowflake with assurance that data ingestion is reliable, scalable and optimized for performance.
4. Data Modelling and Design: With requirements from business, design and implement data models within Snowflake, including schema design, table structures and data partitioning to support high performance, low latency querying and analytics.
5. Data Quality and Integrity: Enforce data quality checks and validation during data ingestion process to ensure accuracy and integrity of data in Snowflake.
6. Support Continuous Improvement in Data Product: Support the Commercial Analytics in advancing continuous improvement in the data space, including team engagement to generate awareness of initiatives and track progress.
7. Monitoring and Maintenance: Proactively monitor data pipelines and the overall health of Snowflake data infrastructure to identify and resolve issues.
8. Automation and Orchestration: Automate data workflows and orchestrate data processes to minimize manual intervention and improve operational efficiency.
9. Collaboration with Data Users: Work closely with data analysts, data engineers, and business users to understand their data requirements and provide necessary data support.

Qualifications & experience

• Tertiary qualification in Data Analytics or related discipline
• 3 to 7 years of data engineering experience in Snowflake
• 3 to 7 years of experience in the downstream oil industry and/or petroleum trading companies in areas such as Supply planning, Supply operations, line finance roles, corporate planning and strategy, and distribution and sales leadership positions.

Knowledge & Skills

• Proficiency in programming languages like SQL to work with database sets and data manipulation.
• Solid understanding of database management systems, data storage, data indexing and query optimization for efficient data handling.
• Proficient in data modelling techniques and design patterns to help create efficient and scalable data architectures.
• Effective communication skills and the ability to collaborate with cross-functional teams to understand data requirements and deliver valuable insights.
• Understanding of data quality principles and data governance best practices.
• Proficiency in data analytics languages like Python, Java, Scala, etc.
• Knowledge of big data technologies like Hadoop, Spark and distributed computing frameworks to manage large scale data processing.
• Proficient in using version control systems like Git for managing code and configurations.
• Stay updated with latest data trends, technologies and best practices in data engineering.

Want to take your career to the next level? Apply today.