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Fidelity International

Investment management and retirement solutions provider

Senior Technical Analyst

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent experience.
  • Five to eight years of experience in software development, data engineering, cloud engineering, technical analysis, or a related role.
  • Strong hands-on experience with Python and SQL.
  • Experience developing and supporting data pipelines, automation, and system integrations.
  • Experience with Git, continuous integration and continuous delivery, automated testing, logging, and production support.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Ability to translate requirements into technical specifications and working solutions.
  • Strong communication and stakeholder-management skills.
  • Ability to work independently while contributing to team delivery and technical standards.
  • Experience deploying or supporting workloads on AWS.

Responsibilities

  • Translate business and technical requirements into practical solution designs and implementation plans.
  • Provide day-to-day technical guidance and support delivery planning, prioritization, and dependency management.
  • Review technical solutions for alignment with engineering, architecture, security, and data standards.
  • Communicate delivery progress, risks, dependencies, and production issues to stakeholders.
  • Support code reviews, knowledge sharing, mentoring, and continuous improvement.
  • Develop, deploy, and support production machine learning models, analytical solutions, and data pipelines.
  • Build Python- and SQL-based automation, integrations, and data-processing components.
  • Support data ingestion, transformation, and processing across AWS, Snowflake, and Informatica Cloud.
  • Implement model versioning, testing, deployment, monitoring, and documentation practices.
  • Promote data quality, lineage, source-to-target mapping, and clear production ownership.
  • Support approved generative and agentic AI solutions, including retrieval workflows, enterprise data connections, tool integrations, and monitoring.
  • Deploy and operate machine learning, data, and AI workloads on AWS.
  • Develop and maintain continuous integration and continuous delivery pipelines, containerized solutions, and infrastructure automation.
  • Work with AWS services such as SageMaker, Bedrock, S3, Lambda, ECS, EKS, and CloudWatch.
  • Implement logging, monitoring, alerting, cost controls, and operational runbooks.
  • Coordinate production releases, deployment validation, incident investigation, and operational handover.
  • Troubleshoot application, data, infrastructure, and model-processing issues and perform root-cause analysis.
  • Collaborate with Architecture, Security, Cloud, and Data teams to deliver reliable production solutions.

Desired Qualifications

  • Experience with AWS SageMaker, Amazon Bedrock, S3, Lambda, ECS, EKS, or CloudWatch.
  • Experience with Snowflake and Informatica Cloud.
  • Experience with Docker, infrastructure as code, and workflow orchestration.
  • Experience operationalizing machine learning models and implementing MLOps practices.
  • Experience with generative AI, retrieval-augmented generation, vector search, or agent-based solutions.
  • Experience with REST APIs, enterprise integrations, and cloud-security practices.
  • Experience with data quality, lineage, metadata, and source-to-target mapping.
  • AWS, Snowflake, Informatica, DevOps, or data-engineering certifications are considered assets.

About the Company

Fidelity International

Investment management and retirement solutions provider

Fidelity International provides investment solutions and retirement expertise for institutions, individuals, and their advisers around the world. It offers a range of investment management services, personal investing platforms, and retirement savings products, using both its own funds and third-party options. Clients access these tools to pursue long-term financial goals, with revenue coming from management and advisory fees. The company integrates sustainability and responsible investing into its operations and investment processes, aiming to deliver long-term, sustainable outcomes for clients. The goal is to help clients build better financial futures and maintain financial health over time.

Company size
5,001-10,000
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1969

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