Data Analytics Engineer

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About Randstad

Randstad is a global leader in the HR services industry, specializing in temporary and permanent recruitment, including contract staffing of professionals and senior managers. We are experiencing transformational change through the application of Data, Analytics & Automation across all business units.

The Role

We are seeking a talented and motivated Data Analytics Engineer to join our growing Data & AI team. In this role, you will be instrumental in building the data infrastructure, pipelines, and transformations necessary to support our business analytics and reporting needs. You will have the opportunity to work closely with stakeholders across the organization to understand their data requirements and deliver solutions that drive business value.

Key Responsibilities

• Develop and Maintain Data Pipelines:

  Design, build, and maintain robust and scalable data pipelines to ingest, transform, and load data from various sources into our data warehouse.

• Data Modelling and Warehousing:

  Create and optimize data models in Google BigQuery to support reporting, analysis, and data science initiatives.

• SQL Development:

  Write complex and efficient SQL queries to extract, analyze, and transform data, serving as the core of your day-to-day work.

• Python Programming:

  Use Python for data manipulation, scripting, and automation tasks to improve the efficiency of our data workflows.

• Data Analysis & Insight Generation:

  Conduct deep-dive data analysis to uncover trends, patterns, and insights related to client and talent performance.

• Data Visualization & Reporting:

  Build compelling dashboards and reports using data visualization tools. Proficiency in Tableau is preferred, but experience with Looker, Domo, Qlik, Alteryx, or Power BI is also highly valued.

• Collaboration:

  Work closely with stakeholders, business analysts, and data scientists to understand business needs and translate them into technical requirements.

• Governance:

  Ensure data is compliant with relevant policies and local laws.

Skills and Experience

• Technical Expertise:

  Strong proficiency in SQL is essential, with hands-on experience in a cloud-based data warehouse environment, preferably Google BigQuery.

• Data Transformation:

  Experience with dbt is a significant advantage.

• Programming:

  Solid experience with Python for data-related tasks.

• Data Analysis:

  Proven ability to perform complex data analysis and translate findings into clear, actionable business recommendations.

• Problem-Solving:

  Excellent analytical and problem-solving skills with a keen attention to detail.

• Data Visualization

  : Demonstrated experience in creating interactive and insightful dashboards.

• Communication:

  Strong communication skills, with the ability to explain complex technical concepts to non-technical audiences..

• Self-Managing:

  Effectively manage workload and priorities according to demands and timelines.

Desirable Skills

• Worked within AGILE Scrum framework
• Experience with complex financial data models.
• Hands-on experience with visualization tools like Tableau
• Hands-on experience with Salesforce
• Degree in Computer Science, IT, or a similar field.
• Data engineering certification.
• Knowledge of AI and ML fundamentals.

Personal Attributes

• Naturally curious and skilled at breaking down complex problems and using data to drive decision-making.
• Focused on precision and accuracy.
• Proven ability to work in a close-knit, professional team.
• Proactive and a problem-solver.
• Able to explain complex technical concepts to non-technical stakeholders in a clear and concise manner.
• A natural mentor who enjoys helping others improve and guide teams toward shared goals.
• Takes initiative in identifying issues before they escalate and proposing new solutions or improvements.