Senior Data Engineer

Luxoft; Toronto; On-site; CAD 90,000 - 130,000; Full time

Job summary

Luxoft seeks an experienced Senior Data Engineer to support onboarding, integration, and operationalization of datasets for Middle Office functions. You will build scalable, production-grade data pipelines on AWS (EMR, Glue, Athena, S3) and own the full lifecycle from source analysis through deployment and operations.

The role emphasizes reliable data delivery for analytics, reporting, and downstream applications, with strong focus on data modeling, quality, and DevOps practices using Terraform

Qualifications

• Must have hands-on experience building and operating AWS-based data platforms and data pipelines.
• Advanced expertise with Apache Spark, PySpark, distributed data processing, and performance optimization.
• Experience with modern data lake technologies, particularly Apache Hudi and Apache Iceberg.
• Strong Python programming and software engineering practices, including testing, code quality, and Git-based development workflows.
• Hands-on experience with Apache Airflow or comparable workflow orchestration platforms.
• Experience with Terraform, CI/CD pipelines, and infrastructure automation.
• Ability to independently translate business requirements into production-ready data solutions.

Responsibilities

• Data Onboarding & Integration: Analyze source systems, onboard new datasets, and design scalable ingestion and transformation pipelines to support Middle Office business needs.
• Data Engineering: Develop and maintain production-grade pipelines using AWS services including EMR, Glue, Athena, and S3, leveraging Spark/PySpark and modern data lake technologies.
• Workflow Automation: Build and manage orchestration workflows using Airflow or equivalent platforms, including scheduling, monitoring, alerting, and recovery processes.
• Data Architecture & Modeling: Design scalable data models, schema structures, partitioning strategies, and data quality controls to ensure reliable and efficient data consumption.
• DevOps & Operational Excellence: Implement CI/CD pipelines and infrastructure-as-code practices using Terraform and GitHub Actions, ensuring maintainable and supportable solutions.
• Production Support: Troubleshoot data quality, performance, and operational issues while driving long-term reliability improvements.

Skills

AWS data pipelines

Spark / PySpark

Python programming

Airflow

Terraform

CI/CD pipelines

GitHub Actions

Infrastructure as code

Tools

AWS EMR

AWS Glue

AWS Athena

S3

Git

GitHub Actions

Terraform

Job description

Project description

We are looking for an experienced Senior Data Engineer to support the onboarding, integration, and operationalization of datasets used by Middle Office functions. The role focuses on building scalable, production-grade data pipelines and data products on AWS, enabling reliable data delivery for analytics, reporting, and downstream applications. The successful candidate will own the full lifecycle from source analysis and solution design through implementation, deployment, and operational support. The role is for subcontractors.

Responsibilities

• - Data Onboarding & Integration: Analyze source systems, onboard new datasets, and design scalable ingestion and transformation pipelines to support Middle Office business needs.- Data Engineering: Develop and maintain production-grade pipelines using AWS services including EMR, Glue, Athena, and S3, leveraging Spark/PySpark and modern data lake technologies.- Workflow Automation: Build and manage orchestration workflows using Airflow or equivalent platforms, including scheduling, monitoring, alerting, and recovery processes.- Data Architecture & Modeling: Design scalable data models, schema structures, partitioning strategies, and data quality controls to ensure reliable and efficient data consumption.- DevOps & Operational Excellence: Implement CI/CD pipelines and infrastructure-as-code practices using Terraform and GitHub Actions, ensuring maintainable and supportable solutions.- Production Support: Troubleshoot data quality, performance, and operational issues while driving long-term reliability improvements.

SKILLS

Must have

• - Strong hands-on experience building and operating AWS-based data platforms and data pipelines.- Advanced expertise with Apache Spark, PySpark, distributed data processing, and performance optimization.- Experience with modern data lake technologies, particularly Apache Hudi and Apache Iceberg.- Strong Python programming and software engineering practices, including testing, code quality, and Git-based development workflows.- Hands-on experience with Apache Airflow or comparable workflow orchestration platforms.- Experience with Terraform, CI/CD pipelines, and infrastructure automation.- Ability to independently translate business requirements into production-ready data solutions.

Nice to have

We are particularly interested in candidates who have experience building data platforms within financial services, asset management, capital markets, or investment management environments. Experience supporting Middle Office, investment operations, risk, or trading-related datasets is highly desirable. Knowledge of data governance, lineage, security, and large-scale production support is also a strong advantage.