Data Engineer

Google Cloud Platform (GCP)

Apache Airflow, Spark, Python, Scala

Infrastructure as Code (IaC) tools such as Terraform or Ansible

Experience building Customer Data Platforms (CDPs)

Experience with AI-assisted developer tools - IntelliJ plug-ins using OpenAI or Anthropic models, Codex CLI, Windsurf.

Experience – 5 yrs

Canada Remote

Full time requirement

Role Overview:

We’re looking for a skilled Data Engineer to design, build, and optimize scalable, cloud-native data pipelines on Google Cloud Platform (GCP). The role involves extensive work with Apache Airflow, Spark, Python, and Scala to develop high-performance data solutions supporting analytics, streaming, and generative AI initiatives.

Key Responsibilities:

• Develop, automate, and maintain batch and streaming ETL pipelines using Apache Airflow, Apache Spark, Python, and Scala.
• Build and manage cloud-based data ecosystems on GCP (BigQuery, Bigtable, Dataproc, Pub/Sub, Cloud Storage, IAM, VPC).
• Design and optimize SQL and NoSQL data models for data lakes and warehouses (BigQuery, MongoDB, Snowflake).
• Write complex SQL queries for advanced data transformation, aggregation, and analytics optimization within BigQuery or equivalent platforms.
• Apply modern Test Driven Development (TDD) methodologies for big data pipelines, ensuring test automation across Airflow workflows, Spark jobs, and transformation logic.
• Apply data mesh and data-as-a-product principles to enable reusable and domain-driven datasets.
• Implement real time ingestion with Kafka Connect and process streaming data using Spark Streaming, Apache Flink, or similar technologies
• Optimize data performance, scalability, and cost efficiency across GCP components.
• Ensure compliance with PCI and PII data with standards such as GDPR, PCI DSS, SOX, and CCPA.
• Integrate GenAI tools such as OpenAI, Gemini, and Anthropic LLMs for intelligent data quality and analytics enhancement.
• Collaborate with stakeholders, data scientists, and full stack engineers to deliver trusted, documented, and reusable data products

Required Qualifications:

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
• 5+ years of hands-on experience with large-scale data engineering in cloud environments.
• Advanced skills using Python, Scala, Spark ecosystem, SQL to build data pipelines
• Strong GCP expertise (BigQuery, Bigtable, Dataproc, Pub/Sub, IAM, VPC).
• Proficiency in SQL/NoSQL modeling and data architecture for cloud data lakes.
• Familiarity with streaming frameworks (Kafka, Flume).
• Experience handling sensitive data and ensuring regulatory compliance.
• Working knowledge of Docker, CI/CD, and modern DevOps practices for data platforms.

Preferred Qualifications:

• Experience with Infrastructure as Code (IaC) tools such as Terraform or Ansible.
• Contributions to open-source projects or internal developer tooling.
• Prior experience building Customer Data Platforms (CDPs) inhouse
• Experience with AI-assisted developer tools (for example, IntelliJ plug-ins using OpenAI or Anthropic models), Codex CLI, Windsurf.

Job Type: Full-time

Pay: $70,503.61-$150,613.77 per year

Work Location: Remote