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Marex

Senior DataOps Engineer

Posted 5 Hours Ago
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In-Office
London, Greater London, England, GBR
Mid level
In-Office
London, Greater London, England, GBR
Mid level
The DataOps Engineer will design and operationalize DataOps frameworks, build CI/CD pipelines, enforce data reliability, and provide technical leadership in data, AI/ML, and analytics.
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About Marex

Marex Group plc (NASDAQ: MRX) is a diversified global financial services platform providing essential liquidity, market access and infrastructure services to clients across energy, commodities and financial markets. The group provides comprehensive breadth and depth of coverage across four core services: clearing, agency and execution, market making, and hedging and investment solutions. It has a leading franchise in many major metals, energy and agricultural products, with access to 60 exchanges. The group provides access to the world’s major commodity markets, covering a broad range of clients that include some of the largest commodity producers, consumers and traders, banks, hedge funds and asset managers. With more than 40 offices worldwide, the group has over 3,000 employees across Europe, Asia and the Americas.

For more information visit https://www.marex.com/

Position Reference: VN2644

Department description

Marex has unique access across markets with significant share globally both on and off exchange. The depth of knowledge amongst its teams and divisions provides its customers with clear advantage, and its technology-led service provides access to all major exchanges, order-flow management via screen, voice and DMA, plus award-winning data, insights and analytics.

Marex has unique access across markets with significant share globally both on and off exchange. The depth of knowledge amongst its teams and divisions provides its customers with clear advantage, and its technology-led service provides access to all major exchanges, order-flow management via screen, voice and DMA, plus award-winning data, insights and analytics.

The Technology Department, delivers secure, scalable digital tools, software services, and infrastructure across all business units. Agile development teams align with specific business areas, while other teams handle enterprise-wide IT operations, support, security, and architecture.

The Data & AI team drives productivity, compliance, and insights by leveraging a robust Data Lakehouse, decentralizing data access, improving client experiences, promoting data-driven practices, and ensuring efficient, auditable use of data in line with commercial terms.

Role Summary

We are seeking a DataOps Engineer to own and embed a DataOps way of working across the enterprise data organisation. This is a greenfield role with a clear organisational mandate and significant scope to define how DataOps frameworks, tooling, and engineering standards are applied across our data platforms.

The role is accountable for enabling the safe, reliable, and frequent delivery of production grade data capabilities, supporting real-time management information, critical systems integration, advanced analytical and ML model refreshes, and accurate, timely data for customer facing AI solutions.

Acting as a force multiplier for Data Engineering, AI/ML Engineering, and Analytics teams, the role combines deep technical leadership with senior level stakeholder engagement, shaping a culture of quality, automation, and operational excellence while translating governance, risk, and control requirements into engineering patterns that scale effectively and support delivery at the pace of the business.

Responsibilities

Role specific:

  • Design, implement, and operationalise the DataOps target state through consistent frameworks, tooling, and standards aligned with enterprise architecture, governance, and assurance requirements.
  • Build and maintain CI/CD pipelines for data and ML workloads, enabling controlled, automated promotion across development, staging, and production environments.
  • Enforce separation of duties between engineering and production administration to support regulatory, risk, and operational assurance requirements.
  • Define and implement test‑driven development practices for data pipelines, including unit, integration, and end‑to‑end testing.
  • Embed data reliability patterns aligned to the Medallion Architecture (Bronze, Silver, Gold). · Implement data quality enforcement, monitoring, and observability frameworks to improve platform trust and stability.
  • Apply software engineering and SDLC best practices consistently across data and ML workloads.
  • Provide hands‑on technical leadership and design advisory services to Data Engineering, AI/ML Engineering, and Analytics teams, ensuring solutions align with DataOps standards and patterns.
  • Build and maintain reusable DataOps toolkits, templates, and reference architectures to accelerate adoption and consistency.
  • Partner with Governance, Risk, and Control stakeholders to translate policy and regulatory requirements into pragmatic, repeatable engineering controls.
  • Support production readiness, release governance, and post‑incident learning for data platforms, contributing to continuous improvement in scalability, resilience, and operational excellence.
  • Champion DataOps, analytics, and engineering best practices across technical and business teams, promoting a culture of automation, quality, and disciplined delivery.

All staff:

  • Ensure compliance with the company’s regulatory requirements under the FCA.
  • Adhere to the operational risk framework for your role ensuring that all regulatory or company determined parameters are complied with.
  • Role model for demonstrating highest level standards of integrity and conduct and reflecting Company Values.
  • At all times comply with the FCA’s Code of Conduct.
  • Ensure that you are fully aware of and adhere to internal policies that relate to you, your role or any other activities for which you have any level of responsibility.
  • Report any breaches of policy to Compliance and/ or your supervisor as required.
  • Escalate risk events immediately.
  • Provide input to risk management processes, as required.

Competencies, Skills, Experience & Qualifications:

Competencies:

  • Excellent verbal and written communication skills.
  • A collaborative team player, approachable, self-efficient and influences a positive work environment.
  • Demonstrates curiosity.
  • Resilient in a challenging, fast-paced environment.
  • Ability to take a high level of responsibility in a fast pace and high-volume environment.
  • Excels at building relationships, networking and influencing others.
  • Strategic collaborator with insight and agility, able to anticipate future challenges, ensuring operational effectiveness.

Skills and Experience:
Essential:

  • Strong experience implementing DataOps or DevOps practices in complex data environments.
  • Proven expertise designing and operating CI/CD pipelines for data and analytics workloads. Hands‑on experience with Databricks (AWS and/or Azure) in production environments. · Strong proficiency in Python and SQL.
  • Experience applying Infrastructure as Code (IaC) using tools such as Terraform.
  • Deep understanding of data platform reliability, observability, and quality controls.
  • Strong knowledge of software engineering best practices and SDLC.
  • Ability to operate as both hands‑on engineer and strategic enabler.
  • Experience working in a regulated environment and knowledge of the risk and compliance requirements associated with this.

Desirable:

  • Experience in financial services, with exposure to ETD and OTC derivative markets highly desirable.
  • Hands‑on experience with:
    - Orchestration Platforms such as Azure Data Factory and Apache Airflow
    - Databricks Asset Bundles
    - Power BI
    - Data Transformation Platforms such as dbt and Databricks Lakeflow
  • Experience with Azure DevOps (ADO), Bitbucket, and Git‑based workflows.
  • Advanced use of VS Code and developer productivity tooling (e.g. GitHub CoPilot). Experience supporting ML pipelines and model lifecycle operations. 
  • Prior involvement in building or scaling enterprise data platforms.
  • Databricks Certified Data Engineer Professional.
  • DAMA Certified Data Management Professional (CDMP).

Conduct Rules, You must:

  • Act with integrity
  • Act with due skill, care and diligence
  • Be open and cooperative with the FCA, the PRA and other regulators
  • Pay due regard to the interests of customers and treat them fairly
  • Observe proper standard of market conduct
  • Act to deliver good outcomes for retail customers

Company Values

Acting as a role model for the values of the Company:

Respect - Clients are at the heart of our business, with superior execution and superb client service the foundation of the firm. We respect our clients and always treat them fairly.

Integrity- Doing business the right way is the only way. We hold ourselves to a high ethical standard in everything we do – our clients expect this and we demand it of ourselves.

Collaborative- We work in teams - open and direct communication and the willingness to work hard and collaboratively are the basis for effective teamwork. Working well with others is necessary for us to succeed at what we do.

Developing our People- Our people are the basis of our competitive advantage. We look to “grow our own” and make Marex the place ambitious, hardworking, talented people choose to build their careers.

Adaptable and Nimble- Our size and flexibility is an advantage. We are big enough to support our client’s various needs, and adaptable and nimble enough to respond quickly to changing conditions or requirements. A non-bureaucratic, but well controlled environment fosters initiative as well as employee satisfaction.

Marex is fully committed to being an inclusive employer and providing an inclusive and accessible recruitment process for all. We will provide reasonable adjustments to remove any disadvantage to you being considered for this role. We value the differences that a diverse workforce brings to the company.  We welcome applications from candidates returning to the workforce.  Also, Marex is committed to avoiding circumstances in which the appearance or possibility of conflicts of interest may exist within the hiring process.

If you would like to receive any information in a different way or would like us to do anything differently to help you, please include it in your application.

Top Skills

Apache Airflow
AWS
Azure
Azure Data Factory
Azure Devops
Ci/Cd
Databricks
Databricks Lakeflow
Dataops
Dbt
DevOps
Git
Power BI
Python
SQL
Terraform

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