Hello, we are Averis!

Averis Information Technology is a global IT services organization headquartered in Kuala Lumpur that designs and delivers IT solutions for large enterprises, to drive economies of scale and business transformation. Our core areas of expertise are: infrastructure and networking, ERP and procurement systems, cybersecurity and data governance, digital workplace and end-user management. Our journey started in 2006, and today, more than 300 IT professionals are servicing major customers in resource-based manufacturing industries such as i.e. paper, packaging and tissue, edible oils, and energy which collectively encompass $35B of assets and 80,000 employees sited across 32 locations globally.

Key Responsibilities:

Collaborate with cross-functional teams to understand data requirements and design efficient data pipelines.
Develop, implement, and maintain ETL (Extract, Transform, and Load) processes to collect, clean, and store data from various sources.
Optimize and enhance existing data pipelines for better performance, scalability, and reliability.
Ensure data quality and integrity through data validation, monitoring, and error handling.
Troubleshoot and resolve data-related issues in a timely manner.
Collaborate with data scientists and analysts to provide the necessary data sets and tools to perform advanced analytics and reporting.
Implement data security and privacy best practices to protect sensitive information.
Stay updated with the latest trends and technologies in data engineering and contribute to the continuous improvement of our data infrastructure.
Must have hands-on experience with Databricks for building and optimizing data pipelines and performing data engineering tasks.

Skills & Qualifications

Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent work experience).
5+ years of experience in data engineering or a related role.
Proficiency in programming languages such as Python, Java, or Scala.
Strong experience with data warehouse technologies (e.g., AWS Redshift, Google BigQuery, Snowflake).
Hands-on experience with ETL tools and frameworks (e.g., Apache Spark, Apache NiFi).
Experience with Databricks and its integration with data engineering tasks.
Knowledge of database systems (SQL and NoSQL) and data modeling.
Familiarity with data integration and orchestration tools (e.g., Apache Airflow).
Understanding of data security and compliance standards.
Excellent problem-solving and communication skills.
Ability to work independently and collaboratively in a fast-paced environment.
Strong attention to detail and a commitment to delivering high-quality work.
Experience with version control systems (e.g., Git).

Nice to Have

Experience with finance/ERP data sources such as SAP (e.g., S/4HANA or ECC modules like FI/CO, SD, MM; SAP BW/4HANA).
Understanding of common finance data models and entities (e.g., GL, AP/AR, Cost Centers, Profit Centers, COPA).
Experience integrating SAP or other ERP systems with data lakes/warehouses and building reliable, auditable pipelines.
Familiarity with financial governance and controls (e.g., SOX, data lineage, reconciliations).

Senior Data Engineer (Finance Analytics)