Data Engineer
Four Eyes Financial
- Moncton, NB
- Permanent
- Full-time
- Architect, build, and maintain a scalable Data Lakehouse using AWS S3, Apache Iceberg, and AWS Glue.
- Develop and operate robust, continuous ETL pipelines to ingest high-volume data from various sources, including Aurora databases using AWS Database Migration Service (DMS).
- Collaborate with the AI team to prepare, structure, and contextualize data for training and fine-tuning Large Language Models (LLMs) and specialized AI agents.
- Contribute to the implementation and maintenance of the MLOps environment, ensuring proper version control for datasets and models.
- Utilize Amazon Neptune to model and manage the complex permissions graph required for secure data access.
- Experience with large data sets and Enterprise-grade databases (Relational, NoSQL and Node Graph Databases).
- Experience with many data types: JSON, XML, CSV, etc.
- Deep understanding of how to build and maintain event driven ETL processes with complex interdependencies.
- Understanding of how to implement ETL processes using a combination of serverless and container-based infrastructure.
- Experience architecting and building data pipelines.
- Experience extracting data from multiple sources (APIs, SFTP, Web Scraping, etc.).
- Participate in sprint planning, peer code reviews, and architectural discussions.
- Contribute to a fast-paced team solving complex business challenges with AI, ensuring alignment with product and project goals.
- Document model development and decision-making processes clearly.
- Support team members in learning best practices in AI development.
- Contribute to a culture of learning and innovation within the team.
- A graduate of Computer Science, Engineering or equivalent knowledge/experience; with a minimum of 5 years of experience.
- Strong programming skills in Python and advanced proficiency in SQL (Postgres experience is an asset).
- Proven experience building and operating ETL pipelines using cloud-based tools such as AWS Glue, AWS DMS, Apache Airflow, or similar technologies.
- Solid experience within the AWS data ecosystem (e.g., S3, Glue, Lambda).
- An intuitive grasp of data modeling, data warehousing, and Data Lakehouse concepts.
- Familiarity with Python libraries for data manipulation such as Pandas, NumPy, or Dask.
- Experience with Amazon SageMaker, Amazon Bedrock, Amazon OpenSearch, or graph databases like Amazon Neptune.
- Experience with Python coding frameworks such as Flask or FastAPI.
- Bonus: Experience in fintech or regulatory/compliance-driven environments.
- Group health & dental benefits
- RRSP matching program
- Competitive salary & vacation days
- Hybrid work options
- And more!