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Luxoft

Senior Data Engineer

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 6, 2026
Posting language: English
Posted: Oct 7, 2026

Original job description

Project Description:

We are seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management Technology team. This role focuses on implementing reliable data solutions in a cloud-native environment using established platform tooling and patterns. You are expected to independently design and deliver data solutions with minimal oversight.
This is not a role for someone who requires detailed task breakdowns or constant direction. Once objectives and constraints are clear, you are expected to independently drive work to completion, proactively manage risks, communicate progress and trade-offs effectively, and manage stakeholder expectations.

Responsibilities:

Own timelines and deliverables, proactively managing scope, dependencies, and execution risks
Independently frame, design, and deliver software solutions by engaging stakeholders, clarifying ambiguous requirements, and challenging assumptions
Build backend services and RESTful APIs aligned to those designs
Develop cloud-native applications (AWS preferred)
Implement workflow automation and data pipelines where needed
Contribute across the full software development lifecycle, including CI/CD
Ensure solutions are production-ready, including testing, documentation, and handover
Act as a reliable execution partner, proactively communicating progress, trade-offs, risks, and changes in expectations

Mandatory Skills Description:

Strong Python with PySpark
Hands-on experience with Databricks, including developing and operating data workloads
Schema design and data modelling experience
Working knowledge of Spark sufficient to build and troubleshoot PySpark workloads; deep Spark specialization is not required
Prior consulting, advisory, or client-facing delivery experience
Proven ownership and independent delivery without close supervision
Strong problem-solving skills, including the ability to frame and solve problems in ambiguous situations
Strong communication and stakeholder management skills, including proactive expectation management
Demonstrated adoption of AI-assisted engineering tools and practices as part of day-to-day engineering delivery

Nice-to-Have Skills Description:

Experience with Apache Iceberg · AWS data services (Glue, Lake Formation) · Workflow orchestration tools (Airflow) · Experience with distributed data processing architectures · Capital markets experience

Languages:

English: C1 Advanced

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More about this job

Responsibilities

Independently design and deliver cloud-native data solutions, backend services, RESTful APIs, and data pipelines, owning timelines, scope, dependencies, and execution risks. Ensure production readiness through testing, documentation, CI/CD, and handover while proactively communicating progress, trade-offs, and risks to stakeholders.

Requirements

Requires strong Python and PySpark skills, hands-on Databricks experience, data modeling and schema design knowledge, and working knowledge of Spark. Candidates must demonstrate independent delivery, problem-solving in ambiguous situations, client-facing experience, strong communication and stakeholder management, and adoption of AI-assisted engineering tools.

Skills

Python
PySpark
Databricks
Spark
Data Modeling
Schema Design
RESTful APIs
AWS
Data Pipelines
Workflow Automation
CI/CD
Problem-Solving
Stakeholder Management
Independent Delivery
AI-Assisted Engineering

Visa sponsorship

Not detected in the job text

Keywords

Python
PySpark
Databricks
Apache Spark
Apache Iceberg
AWS
AWS Glue
AWS Lake Formation
Airflow
Data Engineering
Data Modeling
Schema Design
RESTful APIs
Backend Services
Cloud-Native Applications
Data Pipelines
Workflow Automation
Distributed Data Processing
CI/CD
Testing
Documentation
AI-Assisted Engineering
Capital Markets
Stakeholder Management
Client-Facing Delivery

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