Data Engineer – Design and Build Scalable Data Pipelines

About the role

Particle41 is looking for a talented Data Engineer to design, build, and maintain robust data pipelines and infrastructure. You will work across the full data lifecycle, from raw ingestion to decision‑ready output, supporting client‑facing visualisation and AI‑assisted workflows.

Key responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for large, diverse data sources.
• Build and optimise data lakes and data warehouses for efficient storage and retrieval.
• Integrate structured and unstructured data into unified views for analysis.
• Ensure data accuracy, consistency, and completeness through validation, cleansing, and transformation.
• Document data processes, tools, and systems clearly.
• Create and maintain Tableau dashboards and reports, designing data models for optimal performance.
• Support AI/ML workflows by providing clean data for model training, inference, and evaluation.
• Collaborate with product managers and stakeholders to gather requirements and translate them into technical solutions.
• Participate in Agile ceremonies, deliver on time, and adapt to shifting priorities.
• Write unit and integration tests, debug pipelines, and resolve performance or quality issues.
• Stay current with cloud platforms (AWS, Azure, GCP) and emerging data engineering tools.

Required profile

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 3+ years of professional experience as a Data Engineer.

Required skills

• Python programming.
• SQL and relational database concepts.
• ETL/ELT pipeline development.
• Data lake and data warehouse design.
• Tableau dashboard creation.
• Cloud platforms: AWS, Azure, GCP.
• Version control (Git).
• Unit and integration testing.
• Agile development methodologies.
• Data validation, cleansing, and transformation techniques.