Data Engineer

On behalf of our client, Manpower is seeking a Data Engineer to join a dynamic and innovative Data Engineering team. The successful candidate will play a key role in designing, building, and maintaining robust data infrastructure, enabling reliable analytics, reporting, and future AI-driven solutions. Working closely with analysts, engineers, and business stakeholders, the Data Engineer will translate business requirements into scalable, high-quality data solutions while helping to ensure the performance, security, and reliability of critical data platforms.

This role requires strong technical expertise, a proactive problem-solving mindset, and a passion for modern data technologies. The position also involves participation in a 24×7 on-call roster, supporting business-critical systems and ensuring service continuity outside standard working hours.

Key Responsibilities

• Develop a strong understanding of diverse data sources to design, build, and maintain reliable data pipelines and processing frameworks.
• Collaborate with data analysts and stakeholders to gather requirements and translate them into effective technical solutions.
• Design, build, and maintain the data warehouse, data lakehouse, and related data repositories.
• Architect data pipelines around built-in provenance, stable record identities, idempotent operations, explicit reprocessing rules, and observable, replayable failures.
• Optimise existing pipelines and create new ones to ensure performance, scalability, and reliability.
• Ensure high data quality and integrity through validation, cleansing, and monitoring processes.
• Implement and maintain data security, governance, and privacy best practices across all systems.
• Learn and gain hands-on experience with the existing data warehouse and analytics environment.
• Stay up to date with advancements in data engineering, analytics platforms, and AI foundations to help build future-ready solutions.

Technology Stack

Programming & Scripting

• Linux shell scripting, Python, Bash, PL/SQL

ETL / ELT & Data Processing

• Airflow, dbt, dlt, Kafka, Pulsar, PySpark, Dremio, Talend

Databases & Storage

• Oracle, PostgreSQL, MariaDB
• Iceberg Tables
• AWS S3 and modern data lake architectures
• Columnar Databases

Development & Collaboration Tools

• GitLab, Docker, VS Code
• JIRA, Confluence, SharePoint

BI & Reporting

• Familiarity with SAP BusinessObjects or Power BI

Skills, Behaviour & Competencies

• Strong analytical skills with the ability to identify requirements and design effective solutions.
• Self-starter with the ability to work independently and take initiative.
• Collaborative team player who thrives in cross-functional environments.
• Fast learner with the ability to quickly acquire new technical skills and knowledge.
• Strong planning and prioritisation skills to manage multiple tasks and deadlines.
• Creative problem-solver with a continuous improvement mindset.
• Genuine curiosity for data and enthusiasm for laying the foundations for AI-enabled technologies.

Experience & Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a Data Engineer or in a similar technical role.
• Strong proficiency in SQL and Python.
• Hands-on experience with data warehousing and data lake technologies (e.g. Dremio, Snowflake, Databricks, AWS S3).
• Hands-on experience with high-performance columnar databases for OLAP and real-time analytics (e.g. ClickHouse or Apache Doris).
• Experience with cloud platforms and containerisation/orchestration technologies such as Kubernetes.
• Experience developing and deploying modern data tools (e.g. Airflow, dbt, dlt, Python frameworks) using GitOps continuous delivery practices (e.g. Argo CD, Flux) within Kubernetes environments.
• Solid understanding of data modelling, data warehousing, and data lakehouse concepts.
• Experience with Linux operating systems is considered an asset.
• Knowledge of telecommunications systems and database administration is considered advantageous.
• Strong communication skills with the ability to collaborate effectively across technical and non-technical teams.