Senior Software Engineer - Data Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer – Data Platform based in Canada.

This is a high-impact engineering role focused on building and scaling the foundational data infrastructure that powers large-scale analytics, machine learning, and product innovation. You will work on distributed systems that process and move petabytes of data across modern cloud environments, enabling real-time insights and data-driven decision-making across global operations. The role sits at the heart of a fast-growing, mission-driven engineering organization where data is central to product development and customer value. You will design and operate highly scalable ingestion, processing, and lakehouse systems that support both internal teams and customer-facing features. The environment is highly technical, collaborative, and focused on long-term scalability, reliability, and performance. You will have the opportunity to work closely with engineers, data scientists, and infrastructure teams while shaping the future of a next-generation data platform.

Responsibilities

• Design, build, and operate large-scale data ingestion and replication systems from production sources (e.g., relational databases, NoSQL stores, APIs, and event streams) into a modern data lakehouse architecture.
• Develop and maintain distributed data processing infrastructure using technologies such as Apache Spark and Databricks, ensuring high reliability, scalability, and performance at petabyte scale.
• Improve platform observability, security, developer experience, and operational excellence across core data infrastructure systems.
• Build internal tools, libraries, APIs, and frameworks (primarily in Go, Python, or similar languages) to enable efficient and secure data access and processing across engineering teams.
• Contribute to the design and evolution of lakehouse infrastructure, including data catalogs, metadata systems, orchestration tools, and cloud storage solutions.
• Collaborate cross-functionally with product engineering, infrastructure, security, data science, and analytics teams to deliver robust, scalable data solutions.
• Participate in shaping long-term data platform strategy, including support for AI-driven workloads, global scalability, privacy, and emerging data technologies.

Requirements

• 4+ years of professional software engineering experience in production environments, with a strong focus on distributed systems or data infrastructure.
• 4+ years of experience building or operating large-scale data platforms, ingestion pipelines, or data lake/lakehouse systems.
• Strong hands-on experience with Apache Spark or comparable distributed data processing frameworks.
• Solid experience working within AWS environments, including services such as S3, RDS, DynamoDB, SQS, Kinesis, or Lambda.
• Proficiency in at least one production-grade programming language such as Go, Python, Scala, or Java.
• Proven ability to design scalable, reliable systems with strong emphasis on observability, performance, and operational excellence.
• Experience collaborating effectively with cross-functional stakeholders including engineers, data scientists, analysts, and security teams.
• Nice to have: experience with Databricks, Delta Lake, Iceberg, or Hudi; data ingestion systems; orchestration tools (Airflow, Dagster, Prefect); infrastructure-as-code (Terraform, CloudFormation); and containerization (Docker, Kubernetes, ECS, Fargate).
• Strong communication skills and a collaborative mindset, with the ability to work in fast-paced, high-scale engineering environments.

Benefits

• Annual base salary range: $130,900 – $220,000 USD , with additional equity (RSUs) and performance-based compensation opportunities
• Equity grants with ongoing refresh programs tied to performance
• Flexible, remote-friendly working model with options for in-office collaboration where applicable
• Comprehensive health, dental, vision, and parental leave benefits
• Professional development stipend to support continuous learning and career growth
• High-impact engineering environment focused on large-scale distributed systems and real-world infrastructure challenges
• Opportunity to work on cutting-edge data platforms powering global physical operations

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role\'s core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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