Principal Software Engineer, BI & Data Platform

Calabrio

Workable workplace: remote Workable remote: True Workable locations: Toronto, Ontario, CanadaFull-TimePrincipal

SalaryAt least 120,000 USD per year

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Job Details

Experience: 10+ years of professional experience in software development, with at least 5 years focused on data engineering, business intelligence, or analytics platforms in enterprise SaaS environments.
Required Skills: AWSPostgreSQLPythonSQLAgileDynamoDBFlaskJavascriptKafkaTypeScriptFastAPIReactCI/CDRESTful APIsTerraformRedshiftCloudFormationPlaywright

Requirements

10+ years of professional experience in software development, with at least 5 years focused on data engineering, business intelligence, or analytics platforms in enterprise SaaS environments.
Deep expertise in AWS data and analytics services including Athena, Redshift, Glue, S3, QuickSight, Lake Formation, with hands-on experience architecting and operating production workloads.
Advanced proficiency in Python for data processing, ETL/ELT development, and backend services, with strong knowledge of frameworks such as FastAPI, Flask, or similar.
Expert-level SQL skills including complex query optimization, window functions, CTEs, and performance tuning across multiple database engines (Redshift, PostgreSQL, Athena).
Strong full-stack development capabilities with proficiency in React, JavaScript/TypeScript, and modern front-end frameworks for building analytics dashboards and data visualization interfaces.
Proven experience with Apache Iceberg, Parquet, or similar columnar formats and modern data lake architectures.
Deep understanding of data modeling techniques for both OLTP and OLAP workloads, including dimensional modeling, star/snowflake schemas, and denormalization strategies.
Strong, in-depth experience with AI coding assistants such as GitHub Copilot, Cursor, and Windsurf to accelerate development and improve code quality.
Experience with both relational databases (Redshift, PostgreSQL, Aurora) and non-relational databases (DynamoDB, OpenSearch, DocumentDB).
Demonstrated ability to design and implement scalable REST APIs, event-driven architectures (Lamda, EventBridge, SQS, SNS), and microservices patterns.
Experience with AWS CDK (Cloud Development Kit) or CloudFormation/Terraform for infrastructure-as-code and automated deployment pipelines.
Strong background in data pipeline orchestration using AWS Step Functions, Glue workflows, or similar tools.
Proven track record of leading technical initiatives, mentoring senior engineers, and driving architectural decisions in complex distributed systems.
Experience with CI/CD pipelines, automated testing frameworks (pytest, Playwright), and DevOps practices for data platforms.
Excellent problem-solving skills with the ability to troubleshoot complex issues in large-scale, distributed data systems.

Responsibilities

Architect and develop large-scale, mission-critical BI and data platform solutions serving millions of users across the globe, leveraging AWS native technologies including Athena, Redshift, Glue, QuickSight, and S3.
Lead the design and implementation of robust data pipelines, data lakes, and data warehouses using modern architectures (Iceberg, Parquet, columnar formats) to support real-time and batch analytics at scale.
Drive technical strategy and architectural decisions for the BI platform, including data modeling, query optimization, performance tuning, and cost optimization across AWS services.
Build and maintain sophisticated back-end services, ETL/ELT workflows, and front-end analytics applications using Python, SQL, React, and modern web technologies.
Design and implement efficient data storage solutions across relational databases (Redshift, PostgreSQL) and non-relational databases (DynamoDB, S3), ensuring optimal performance and cost-efficiency.
Develop and maintain REST APIs and event-driven architectures to enable seamless integration between data services, analytics tools, and customer-facing applications.
Serve as the technical lead and mentor for engineering teams, conducting architecture reviews, code reviews, and providing guidance on complex technical challenges.
Collaborate with cross-functional teams including data engineers, analytics engineers, product managers, and DevOps to deliver innovative BI solutions that drive business value.
Champion engineering excellence by establishing best practices, design patterns, and coding standards for data-intensive applications.
Lead Agile ceremonies, drive sprint planning, and ensure timely delivery of high-quality software solutions while maintaining technical debt at manageable levels.

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