Data Engineer – Cloud & Modern Data Stack

About the role

We are seeking a technically skilled Data Engineer to strengthen our cloud‑based analytics platform. The role focuses on designing, building, and optimizing scalable pipelines and transformation workflows within a modern data stack, leveraging Google Cloud Platform and related tools.

Key responsibilities

• Design, develop, and maintain data pipelines and transformation workflows in cloud analytics environments.
• Build and manage reliable ELT pipelines that ingest data from operational systems, APIs, files, and third‑party platforms into centralized cloud reporting.
• Collaborate with GCP and modern‑stack teams to understand source structures, business logic, and reporting dependencies.
• Develop and optimise SQL queries and transformation logic for processing, reconciliation, modelling, and validation.
• Investigate data discrepancies, reconcile mismatches, and troubleshoot ingestion, transformation, and reporting issues.
• Maintain clear technical documentation covering pipeline logic, source mappings, dependencies, and operational procedures.
• Contribute to data quality and governance by defining control points, validation checks, and testing standards.
• Design, manage, and provision IAM roles and access policies to ensure secure, compliant access to datasets and services.

Required profile

• Strong SQL expertise, including joins, aggregations, performance tuning, and troubleshooting.
• Hands‑on experience with ELT development in cloud‑based analytics environments.
• Good understanding of data structures, modular transformation logic, and pipeline design.
• Ability to translate raw source data into analytical models for reporting.
• Excellent analytical, problem‑solving, and communication skills.

Required skills

• Google Cloud Platform / BigQuery
• dbt
• Airbyte
• Dataform
• ELT development
• IAM role and access policy management