Senior Data Engineer: Greenfield ML Data Lake Architect

Syndesus, Inc.; Canada; On-site; CAD 120,000 - 180,000; Full time

Job summary

Syndesus, Inc. is seeking a Data Engineer to join the ML team and shape the data foundation for model training, inference, and monitoring at scale. You will sit on a greenfield project, owning the Medallion lakehouse on GCP and designing data pipelines for terabytes of data.

You will own data lake layout, ML training pipelines, feature stores (offline/online), and data quality frameworks, while ensuring lineage, observability, and robust CI/CD across the platform.

Qualifications

• 5+ years of software development experience with 3+ years in Data Engineering for ML teams.
• Proven track record building ML training pipelines and data lake/lakehouse architectures.
• Deep Python and SQL proficiency with production-grade code.
• Strong Spark experience for large-scale data processing.
• Hands-on with cloud data warehouses and lakehouse tooling (Snowflake, Databricks, Delta Lake).
• Experience with feature stores, MLOps, data lineage, and data quality checks.
• Kafka or event-driven sources, Airflow or similar orchestration, and CI/CD practices.

Responsibilities

• Own data lake architecture and lay out a Medallion structure for long-term ML use.
• Design ML training pipelines, feeding both structured and unstructured data to models.
• Build and manage offline/online feature stores with trade-offs understood.
• Instrument pipelines with observability, lineage, validation, and quality checks.
• Collaborate with Java teams for Kafka-based data ingestion into pipelines.
• Lead architecture decisions and document trade-offs for scalable systems.
• Apply engineering discipline to data tooling and governance in production.

Skills

Python

SQL

Spark

Data Engineering

ML pipelines

CI/CD

Airflow

Kafka

GCP

Model training

Tools

Snowflake

Databricks

Delta Lake

Feast

Tecton

Airflow

BigQuery

Vertex AI

Cloud Composer

Pub/Sub

Job description

Syndesus, Inc. is seeking a Data Engineer to join the ML team and shape the data foundation for model training, inference, and monitoring at scale. You will sit on a greenfield project, owning the Medallion lakehouse on GCP and designing data pipelines for terabytes of data.

You will own data lake layout, ML training pipelines, feature stores (offline/online), and data quality frameworks, while ensuring lineage, observability, and robust CI/CD across the platform.