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Senior Data Engineer
Senior Data Engineer
Who We Are
Artefact is a new generation of data service provider, specialising in data consulting and data-driven digital marketing. We are dedicated to transforming data into business impact across the entire value chain of organisations. We are enjoying rapid growth.
Our data-driven solutions in consulting and digital marketing are tailored to clients' specific needs, always conceived with a business-centric approach and delivered with measurable results. Our expertise in AI, built through collaborations with 1000+ global clients, powers our scalable offerings.
We have 2000+ employees across 26 offices, focused on accelerating digital transformation. Combining next-gen data technologies, agile AI methodologies, and expert teams of business consultants, data analysts, scientists, engineers, and digital experts, we deliver high-value outcomes to clients.
Job Summary
We are seeking a Senior Data Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a track record of leading high-impact data projects in a fast-paced environment.
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Key Responsibilities
- Design, build, and maintain scalable, robust data pipelines using SQL and Python, leveraging frameworks like:
- Databricks
- Snowflake
- Azure Data Factory
- AWS Glue
- Apache Airflow
- PySpark
- Lead the integration of complex data systems while ensuring consistency, accuracy, and cross-platform alignment.
- Implement CI/CD practices to enhance pipeline efficiency, reliability, and data quality.
- Collaborate with data architects, analysts, and stakeholders to translate business requirements into technical solutions.
- Oversee and mentor a team of data engineers, ensuring high-quality project deliverables.
- Establish and enforce best practices in data governance, security, and compliance.
- Optimise data retrieval performance and develop dashboards/reports for business teams.
- Continuously evaluate and adopt new technologies/tools to strengthen the data engineering function.
Qualifications
Essential
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of industry experience in data engineering, with proficiency in:
- SQL, Python, and big data technologies.
- Scalable data workflows (cloud-native orchestration, distributed processing).
- Experience with Infrastructure as Code (Terraform).
- Strong understanding of CI/CD, DevOps, and DevSecOps.
- Leadership experience in managing data engineering teams.
- Proficient in troubleshooting ambiguity and solving complex technical challenges.
- Skilled in AI-assisted workflows to optimise efficiency.
- Excellent communication skills and interpersonal abilities.
- Deep understanding of data architecture, including data mesh, lake, warehouse, and lakehouse.
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Preferred
- Certifications in Azure, AWS, or Google Cloud (GCP).
- Certifications in Databricks, Snowflake, or related technologies.
- Hands-on experience with large-scale data engineering projects.
Working Conditions
- Hybrid model: 2–3 office days per week.
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