Intermediate Data Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, construct, and sustain scalable and fault-tolerant data pipelines utilizing AWS services.

• Take ownership and advance the architecture for data ingestion, transformation, and storage.

• Create and manage data models, data warehouses, and data marts to facilitate analytics and financial reporting.

• Develop and implement robust ETL processes to guarantee timely, accurate, and auditable data ingestion.

• Collaborate with analytics, finance, product, and engineering teams to convert business requirements into sustainable data solutions.

• Enhance data pipelines and infrastructure for improved performance, reliability, and cost-effectiveness.

• Establish data quality checks, monitoring, and alerting systems to maintain trust in data.

• Ensure data security, integrity, and compliance throughout the entire data lifecycle.

• Construct and oversee data infrastructure using Terraform and adopt infrastructure-as-code practices.

• Support and enhance executive dashboards, financial reporting, and operational analytics.

• Diagnose complex data issues and lead root cause analysis and resolution efforts.

• Mentor junior team members and promote best practices in data engineering across the organization.

• Stay updated with industry trends and continuously enhance data platform capabilities.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.

• Over 3 years of experience in data engineering or developing backend data systems.

• Extensive hands-on experience in designing and managing production data pipelines.

• Deep expertise in SQL and a solid understanding of relational databases.

• Proficient programming skills in Python for data processing and automation tasks.

• Experience with AWS data services, including S3, Aurora, RDS, Lambda, and related tools.

• Familiarity with workflow orchestration tools, preferably Argo Workflows or Airflow.

• Practical experience with PySpark for distributed data processing.

• Proficient in using Terraform or similar infrastructure-as-code tools.

• Strong grasp of data warehousing concepts, dimensional modeling, and ETL best practices.

• Excellent problem-solving abilities with the capacity to evaluate system trade-offs.

• Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.

🏝️ Benefits

• Competitive salaries.

• Excellent health and dental benefits.

• Opportunities and support for ongoing learning, growth, and career development.

• Fully remote work environment.