Data Engineer Lakehouse

About the role

Augmented is hiring a Data Engineer to build and run a modern lakehouse platform for one of our large enterprise clients in a regulated industry. You will design reliable batch and streaming pipelines, model data for analytics and AI use cases, and help retire legacy warehouse workloads.

You will join a small, senior delivery team that works directly with client stakeholders. The work spans greenfield builds and migrations, with a strong focus on data quality, governance and cost.

Key responsibilities

• Design and build lakehouse pipelines using a medallion (bronze/silver/gold) architecture on Delta Lake or Apache Iceberg
• Develop batch and streaming ingestion from databases, APIs, files and event streams (CDC, Kafka)
• Write production-grade PySpark and SQL transformations; tune Spark jobs for performance and cost
• Model curated data sets (dimensional, Data Vault or wide tables) for BI, analytics and ML teams
• Implement data quality checks, lineage and observability; own pipeline SLAs and incident response
• Apply governance and security controls: Unity Catalog or equivalent, row/column-level access, PII handling
• Migrate legacy warehouse and ETL workloads (e.g. Teradata, Oracle, SSIS, Informatica) to the lakehouse
• Build CI/CD for data code and infrastructure-as-code for platform resources
• Partner with client architects, analysts and data scientists; document designs and decisions

Required qualifications

• 4+ years in data engineering, with 2+ years on a lakehouse platform (Databricks, or Spark with Delta Lake/Iceberg)
• Strong Python (PySpark) and advanced SQL
• Hands-on with at least one major cloud: Azure, AWS or GCP (storage, compute, IAM, networking basics)
• Experience with orchestration such as Databricks Workflows, Airflow or Azure Data Factory
• Solid grasp of data modelling, partitioning, file formats (Parquet) and Spark performance tuning
• Git-based workflows and CI/CD (GitHub Actions, Azure DevOps or GitLab)
• Clear communicator, comfortable working directly with enterprise client teams
• Legally entitled to work in Canada

Nice to have

• Databricks Certified Data Engineer (Associate or Professional), or equivalent cloud data certification
• dbt, Delta Live Tables / Lakeflow, or Spark Structured Streaming in production
• Terraform or Bicep for platform provisioning
• Experience in Life Sciences (GxP, clinical or commercial data) or Financial Services (risk, payments, regulatory reporting)
• Exposure to feature stores, vector search or data products for AI/ML
• Consulting or client-facing delivery background

Tech stack

• Platform: Databricks (Unity Catalog), Delta Lake / Apache Iceberg

• Languages: Python (PySpark), SQL

• Cloud: Azure (ADLS Gen2) or AWS (S3)

• Ingestion & streaming: Kafka / Event Hubs, CDC tools, Auto Loader

• Orchestration: Databricks Workflows, Airflow, Azure Data Factory

• Transformation: Spark, dbt, Delta Live Tables

• DevOps: Git, CI/CD pipelines, Terraform

• Consumption: Power BI, Tableau, Databricks SQL

Why Augmented

Augmented is an AI-native engineering delivery hub serving large enterprises in Life Sciences and Fintech, with teams in Toronto and the US.

• Work on high-impact data platforms for enterprise clients
• Small, senior teams with direct access to client decision-makers
• Exposure to AI-native delivery practices and modern tooling
• Compensation: [salary range to confirm] plus benefits