Data Engineer

Job Overview

Aboitiz Data Innovation (ADI) is one of the leading up and coming start-ups in the field of Data Science and Artificial Intelligence. We believe data can drive change for a better world by advancing businesses across industries and communities. We are seeking talented and motivated Data Engineers to join our Data Platform team, who are passionate about defining and implementing information management solutions to address operational needs within businesses.

If you are excited to work in a fast-paced start-up environment, this role will provide a great opportunity to grow your career with us.

As Data Engineer, you will work closely with our Data Scientists and Software engineers to support the design, development, and maintenance of our data infrastructure and Machine learning backend. You will have the opportunity to work with cutting-edge, open sourced technologies and contribute to the growth of our data capabilities, while mentored in all aspects of the data engineering life cycle. You will also gain the hands on experience in driving and leading a project delivery in the data engineering fields.

Responsibilities:

Data Platform / Data Product

• Identify, design, and implement internal automated processes including but not limited to billing, alerts, query usage analysis, storage/compute resource usage analysis
• Ideate, iterate, design and implement features from scratch or based on existing commercial projects that could be provide additional values to the platform users
• Contribute directly or raise feedbacks to our platform features to the Data Infrastructure & Products team to improve our platform efficiency and capabilities.

Commercial Projects

• Lead the delivery of a commercial project end to end
• Collaborate with cross-functional teams to understand data requirements and develop solutions to meet business needs
• Participate and drive the client facing meeting to finalise details, push back on requirements or update status
• Design and implement various data pipelines in a config driven approach, including but not limited to ingestion, transformation and reverse ETL, based on client functional requirements
• Design and implement data quality checks at various checkpoints
• Collaborate with Machine Learning engineers to design, create and maintain various ML data pipelines in a config driven approach, including but not limited to training, batch inference, deployment, validation and monitoring
• Assist in troubleshooting and resolving data-related issues
• Write data quality checks to validate the accuracy, completeness, and consistency of data

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field
• Solid foundation in SQL and Python
• Understanding of conventional database concepts
• Solid understanding of modern data warehouse, lakehouse or lake
• Hands-on experience of cloud platforms (e.g., AWS, Azure, GCP)
• Strong analytical and problem-solving skills
• Experience with implementing Data Quality Checks
• Experience with data processing frameworks (e.g., dbt)
• Experience with data integration and ETL tools (e.g., Airflow)
• Experience with one of the modern warehouse/lakehouse solutions (e.g., Delta Lake, Redshift, Snowflake)
• Experience with Databricks (either Azure or AWS) and a decent understanding of Spark
• Excellent communication and collaboration abilities
• Self-motivated with a passion for learning and continuous improvement
• Knowledge / Experience in the following area is a plus:
  • in one of the MLOps platforms (e.g., MLFlow, Sagemaker)
  • in container technology (e.g., docker, AWS Fargate) and shell scripting
  • In Machine Learning, Data Warehousing (Analytical Engineering) designs or Infra implementations