Data Engineer – Build Scalable Data Pipelines

About the role

Wirestock is a leading data platform that supplies ethically sourced multimodal datasets to top AI labs. We are looking for a Data Engineer to strengthen our data infrastructure, transform raw data into actionable insights, and support internal teams such as product, operations, and leadership.

Key responsibilities

• Troubleshoot and resolve production pipeline issues and data‑quality problems.
• Analyze ingestion and processing failures using logs, system outputs, and internal tools.
• Manage structured and unstructured data, authoring complex JSON configurations for transformations.
• Perform advanced SQL and NoSQL queries (MySQL, MongoDB) for analysis, integrity checks, and validation.
• Utilize AWS S3 for data governance, retrieval, and management.
• Conduct deep‑dive analyses to extract insights that guide product and operational decisions.
• Develop and maintain dashboards and visualizations for internal stakeholders.
• Collaborate with engineering, product, and other teams to define data needs and design scalable reporting solutions.
• Contribute to the design, optimization, and documentation of ETL/ELT pipelines and governance processes.

Required profile

• 4+ years of hands‑on experience in a Data Engineering role.
• Strong attention to detail, data accuracy, and analytical problem‑solving.
• Fluent written and spoken English.

Required skills

• Relational and NoSQL databases – MySQL and MongoDB.
• Advanced SQL proficiency.
• Amazon Web Services – S3 (and general AWS knowledge).
• Complex JSON authoring and troubleshooting.
• Python (or similar scripting language) for data processing.
• ETL/ELT concepts and modern data platform experience.
• Data modeling and understanding of data structures.
• Basic knowledge of Kubernetes and containerised workloads (nice to have).
• Familiarity with workflow orchestration tools such as Argo Workflows or Airflow (nice to have).
• Experience with BI and data‑visualisation tools (nice to have).