Senior Data Engineer
Primary stack
Nice to have's
Job description
About the Position
We are seeking a hands-on Senior 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
Requirements
- 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
- Experience with Apache Iceberg
- AWS data services (Glue, Lake Formation)
- Workflow orchestration tools (Airflow)
- Experience with distributed data processing architectures
- Capital markets experience
We Offer
- Competitive salary
- Opportunity to work in a dynamic and innovative environment
- Professional growth and development opportunities
About the Company
DXC Luxoft is a leading technology services company that helps clients transform their businesses through innovative technology solutions. We are committed to delivering excellence and driving digital transformation.
Application
Interested candidates are encouraged to apply with their resume and cover letter detailing their relevant experience and skills.
Location: Toronto, Canada
Category: Data Science
Employment Type: FULL_TIME
Experience Level: Senior
© Luxoft DXC. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Automotive,Finance,Healthcare,Life Sciences,Tech and Telecom
About the Company Luxoft, a DXC Technology Company, is a global digital strategy and software engineering firm with over 17,000 international employees across 58 offices in 29 countries. Headquartered in Zug, Switzerland, Luxoft specializes in providing tailored tech solutions that drive global business transformation. The company focuses on enhancing customer experiences and boosting efficiency through strategy, consulting, and engineering services. Products, Services & Tech Stack Core Solutions: Digital strategy and software engineering services. Technologies & Frameworks: Specific platforms, languages, or tools are not mentioned in the provided text. Project Scope & Target Clients Client Base: Automotive, finance, healthcare, life sciences, tech, and telecom. Engineering Scale: Scope and complexity of engineering projects are not specified in the provided text.
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