Staff Software Engineer

Jobtailor; Burnaby; On-site; CAD 120,000 - 160,000; Full time

Job summary

Jobtailor is seeking a senior data platform engineer to drive architecture and build scalable data products for analytics and ML. You will mentor engineers, collaborate with data architects and product teams, and shape the real-time streaming and data modeling standards across the platform.

The role requires expert Python and SQL, deep cloud warehouse experience, and strong IaC with Terraform. You will own Airflow orchestration and observability with Datadog, while leading data pipeline

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 10+ years of experience in data engineering or software engineering, with at least 3+ years operating at a senior/staff level.
• Strong proficiency in Python (required) and SQL.
• Expert-level knowledge of cloud data warehouses (e.g., Snowflake, BigQuery).
• Proven track record of designing and scaling data platforms in production environments.
• Strong expertise in data modeling — dimensional modeling, star/snowflake schemas, data vault.
• Extensive experience with workflow orchestration tools (Apache Airflow preferred).
• Strong understanding of streaming technologies (Apache Kafka, Snowpipe) and event-driven architectures.
• Experience with AWS services (S3, MWAA, Glue).Proficiency with Infrastructure as Code (Terraform) and CI/CD tools (CircleCI, Harness, GitHub Actions).
• Experience with Datadog or similar monitoring and observability platforms.

Responsibilities

• Drive the architecture, design, and evolution of our enterprise data platform.
• Set technical direction, mentor engineers, and champion engineering excellence across the team.
• Collaborate with data architects, engineering managers, and product teams.
• Define and deliver the next generation of data products and platform capabilities at scale.
• Design and build scalable data pipelines that power analytics and machine learning.
• Own the design and evolution of workflow orchestration using Apache Airflow.
• Lead the strategy for real-time streaming ingestion using Kafka.
• Champion and advance data modeling standards across the platform.
• Define and implement observability strategy using Datadog.

Skills

Data Engineering

Python Programming

Cloud Data Warehouses

Workflow Orchestration

Data Modeling

Apache Airflow

Apache Kafka

Terraform

CI/CD Tools

Observability

Education

Bachelor's degree in Computer Science/Information Technology or related field

Tools

Snowflake

BigQuery

MWAA

S3

Glue

GitHub Actions

CircleCI

Job description

• Drive the architecture, design, and evolution of our enterprise data platform.
• Set technical direction, mentor engineers, and champion engineering excellence across the team.
• Collaborate with data architects, engineering managers, and product teams.
• Define and deliver the next generation of data products and platform capabilities at scale.
• Design and build scalable data pipelines that power analytics and machine learning.
• Own the design and evolution of workflow orchestration using Apache Airflow.
• Lead the strategy for real-time streaming ingestion using Kafka.
• Champion and advance data modeling standards across the platform.
• Define and implement observability strategy using Datadog.

Requirements

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 10+ years of experience in data engineering or software engineering, with at least 3+ years operating at a senior/staff level.
• Strong proficiency in Python (required) and SQL.
• Expert-level knowledge of cloud data warehouses (e.g., Snowflake, BigQuery).
• Proven track record of designing and scaling data platforms in production environments.
• Strong expertise in data modeling — dimensional modeling, star/snowflake schemas, data vault.
• Extensive experience with workflow orchestration tools (Apache Airflow preferred).
• Strong understanding of streaming technologies (Apache Kafka, Snowpipe) and event-driven architectures.
• Experience with AWS services (S3, MWAA, Glue).Proficiency with Infrastructure as Code (Terraform) and CI/CD tools (CircleCI, Harness, GitHub Actions).
• Experience with Datadog or similar monitoring and observability platforms.

Core Competencies

Demonstrates expertise in designing and evolving enterprise data platforms, with a strong focus on data modeling, workflow orchestration, and real-time streaming ingestion. Proficient in Python, SQL, and cloud data warehouses, while also championing engineering excellence and observability strategies.

Highest-signal resume keywords

• Data Engineering
• Python Programming
• Cloud Data Warehouses
• Workflow Orchestration
• Data Modeling

ATS Optimization Keywords

Hard Skills

• Python
• SQL
• Data Modeling
• Cloud Data Warehouses
• Apache Airflow
• Apache Kafka
• Infrastructure as Code
• CI/CD Tools
• Observability Strategy
• Data Pipelines

Soft Skills

• Mentoring
• Collaboration
• Leadership

Industry Keywords

• Data Platform
• Real-Time Streaming
• Event-Driven Architecture
• Dimensional Modeling
• Star Schema
• Snowflake Schema
• Data Vault

Tools & Technologies

• Datadog
• AWS
• Terraform
• CircleCI
• GitHub Actions