Data Engineering Specialist

Reposted 6 Hours Ago
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Beato António, Lisboa, PRT
In-Office
Mid level
Fintech • HR Tech • Insurance • Consulting
The Role
The Data Engineering Specialist will design data processing systems, create data pipelines, and optimize data management while collaborating with teams and communicating with stakeholders.
Summary Generated by Built In
Company:Mercer

Description:

We are seeking a talented individual to join our Global Data team at Marsh. This role will be based in Lisbon. This is a hybrid role that has a requirement of working at least three days a week in the office.

  

We will count on you to:

  • System Design and Development: Designing and building robust, scalable data processing systems that can handle large volumes of data. This includes databases, data lakes, and other big data infrastructures;

  • Data Pipeline Architecture: Overseeing + hands on in creation and maintenance of efficient data pipelines, which includes tasks such as data extraction, transformation, and loading (ETL);

  • Data Management: Implement data strategies and develop physical and logical data models;

  • Data Optimization: Develop and implement data optimization techniques to improve system efficiency and reduce data latency, complexity, and redundancy;

  • Problem Solving: Use analytical skills to solve complex problems associated with database development and management;

  • Collaboration: Working with other teams, such as data scientists, business analysts, and Qlik Developers, to identify organizational needs and design effective solutions;

  • Innovation: Keeping up-to-date with new technologies and methodologies in the field of data engineering, and fostering a culture of innovation and continuous improvement within the team;

  • Stakeholder Communication: Communicate effectively with both technical and non-technical stakeholders, explaining data infrastructure, strategies, and systems in an understandable way.

What you need to have:

  • Bachelor’s degree in Business Administration, Maths, Engineering, Economics or similar;

  • Advanced Machine Learning Expertise – at least 4 years of strong hands-on experience with core ML algorithms (regression, classification, time-series forecasting) and ability to design, train, and optimize models for real-world problems;

  • Forecasting Project Experience – Proven track record for more than 4 years into building and deploying forecasting models (demand, sales, or time-series) using Python libraries like Pandas, NumPy, Scikit-learn, and stats models;

  • Python Proficiency – Deep knowledge of Python for data analysis, model development, and pipeline automation; experience with clean, modular, and production-ready code;

  • Data Bricks experience;

  • Ability to independently handle the full ML lifecycle: data preprocessing, feature engineering, model building, validation, deployment, and monitoring;

  • Demonstrates curiosity and adaptability, proactively upskills on emerging technologies, tools, and frameworks in ML and data science;

  • Ability to connect technical solutions with business goals, especially in forecasting and decision-making scenarios;

  • Excellent Communication Skills;

  • AI Automation - Develop and maintain AI-driven automation solutions to streamline operational tasks and management information (MI) processes. And integrate internal AI tools with existing systems to enhance data processing and reporting capabilities;

  • Fluent English proficiency;

  • Strong quantitative and analytical skills with ability to translate data into meaningful insights.

What makes you stand out:

  • Experience on leading BI tools like Qlik, Power BI or any other industry preferred BI tool;

  • Aptitude for fostering positive relationships;

  • Teamwork and leadership skills.

Why join our team:

  • We help you be your best through professional development opportunities, interesting work and supportive leaders.

  • We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.

  • Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

Mercer is a business of Marsh (NYSE: MRSH), a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information about Mercer, visit mercer.com, or follow us on LinkedIn and X.

Marsh is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

Skills Required

  • Bachelor's degree in Business Administration, Maths, Engineering, Economics or similar
  • Advanced Machine Learning expertise with 4+ years of experience
  • Proven experience building and deploying forecasting models using Python libraries
  • Deep knowledge of Python for data analysis and model development
  • Experience with Data Bricks
  • Ability to handle the full ML lifecycle independently
  • Excellent communication skills
  • Fluent English proficiency
  • Strong quantitative and analytical skills

Marsh McLennan Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Marsh McLennan and has not been reviewed or approved by Marsh McLennan.

  • Leave & Time Off Breadth Leave offerings are described as generous, including sizable PTO, paid holidays, paid sick days, and additional time off such as paid volunteer time and “Summer days.” These time-off benefits are portrayed as a standout part of the overall rewards package.
  • Healthcare Strength Healthcare coverage is characterized as comprehensive, spanning medical, dental, and vision options, with additional supports like disability and life insurance and access to mental health resources and an EAP. The breadth of plan options is positioned as a core strength of the benefits package.
  • Retirement Support Retirement benefits are framed as solid, with 401(k) programs and employer matching frequently highlighted alongside other financial programs. Stock purchase options are also referenced as an additional wealth-building component of the total rewards mix.

Marsh McLennan Insights

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The Company
HQ: New York, NY
78,000 Employees
Year Founded: 1871

What We Do

Marsh McLennan (NYSE: MMC) brings together nearly 78,000 experts in risk, strategy, and people across Marsh, Guy Carpenter, Mercer, and Oliver Wyman, serving clients in over 130 countries. Marsh enables enterprise worldwide by helping clients manage risks, transforming uncertainty into opportunity. Guy Carpenter helps clients grow profitably with reinsurance broking expertise, advisory services, and advanced analytics. Mercer helps organizations advance the health, wealth, and careers of their most vital asset — their people. Oliver Wyman’s expertise in strategy, operations, risk, and organization transformation changes what is possible for our clients, their industries, and society. Together, we combine a unique range of capabilities to help our clients solve problems, seize opportunities, and build lasting success in increasingly complex operating environments.

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