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Senior Data Engineer
Who We Are
Artefact is a new-generation data service provider, specialising in data consulting and data-driven digital marketing. We focus on transforming data into business impact across organisations’ entire value chain. Driven by explosive growth, we merge state-of-the-art data technologies, agile AI methodologies, and expert consulting—Snowflake. Serving 1000+ global clients, Artefact boasts 2000+ employees across 26 offices.
Our mission? Accelerate digital transformation via cohesive teams of business consultants, data analysts, data scientists, data engineers, and digital experts—working to amplify value for every client.
Job Summary
We’re seeking a Senior Data Engineer to join our team! A leader with expertise in data pipelines, AI-driven workflows, and cloud-native tools—you’ll transform data landscapes while mentoring our engineers. Ready to drive innovation?
Key Responsibilities
- Architect and Build Design scalable, robust data pipelines using SQL/Python +: Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow, or PySpark.
- Integrate & Integrate Some More Oversee complex data system integrations to ensure accuracy, consistency, and unification across platforms.
- CI/CD Everything Implement Continuous Integration/Continuous Deployment (CI/CD) practices to improve pipeline efficiency and data quality.
- Bridge Technical & Business Needs Collaborate with data architects, analysts, and stakeholders—translate requirements into technical solutions.
- Team Leadership Mentor and manage a team of data engineers for high-quality deliverables.
- Data Governance & Security Develop/enforce best practices in data governance, security, and compliance.
- Optimise & Dashboards Refine data retrieval techniques; build dashboards and reports for business teams.
- Stay Futuristic Continuously evaluate new technologies/tools to boost data engineering’s capabilities.
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Qualifications
Essential
- degree: BS/MS in Computer Science, Engineering, or a related field (or equivalent experience).
- Years: 3+ years in data engineering, proficient in SQL, Python, and big data technologies (e.g., Databricks, Snowflake, cloud orchestration tools).
- Tooling: Expertise with Infrastructure as Code (e.g., Terraform).
- CI/CD: Solid grasp of DevOps/DevSecOps and CI/CD.
- Leadership: Proven ability to manage data engineering teams.
- Soft Skills: Acumen for problem-solving, ambiguity, and AI-assisted workflows, plus stellar communication.
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Preferred
- Certifications: Azure, AWS, or GCP and/or Databricks/Snowflake.
- Project Experience: Leadership in large-scale data engineering projects.
Technical Deep Dive
Candidates must demonstrate:
- Experience with data architecture (mesh, lakehouse, warehouse, large-scale lake).
- Exposure/leadership across AI-enhanced data pipeline workflows.
Working Conditions
Flexible hybrid model: 2–3 days on-site (play big team-building games, maybe?), with full remote flexibility for shrinking meetings and freshly baked code.
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