About Wirestock

Wirestock is one of the leading data platforms for ethically sourced multimodal data. We serve some of the world’s top AI labs, including several foundation models, by providing high-quality, fully licensed training datasets. As the AI data landscape undergoes a major shift, we are scaling rapidly to meet rising demand for curated visual data.

About the Role

We are seeking a Data Engineer to join our Data Engineering team and support Wirestock's data infrastructure. This role involves core Data Engineering responsibilities, including building, optimizing, and maintaining scalable data pipelines and a structured data ecosystem.

You will be responsible for transforming raw data into actionable intelligence, analyzing large-scale datasets, and generating insights to support internal teams, including product, content operations, partnerships, and executive leadership.

Key Responsibilities

• Troubleshoot and resolve production data pipeline issues and data quality concerns.
• Analyze and troubleshoot data ingestion and processing failures using technical logs, system outputs, and internal tools.
• Manage and manipulate structured and unstructured data formats, including reviewing and authoring complex JSON configurations for data transformations.
• Perform advanced SQL and NoSQL querying (MySQL, MongoDB) for complex data analysis, integrity checks, and system validation.
• Utilize AWS services (S3) for data governance, retrieval, and management within the data infrastructure.
• Conduct deep-dive data analysis to extract actionable insights that inform product and operational decisions.
• Develop, maintain, and optimize robust data visualizations and dashboards for internal stakeholders.
• Collaborate with Data Engineering, Product, and other teams to define data needs and design scalable reporting solutions.
• Actively contribute to the design, optimization, and documentation of ETL/ELT data pipelines and data governance processes.

Requirements

• 4+ years of hands-on experience in a Data Engineering role.
• Expertise in relational and NoSQL databases, specifically MySQL and MongoDB.
• Advanced SQL proficiency for data manipulation and performance tuning.
• Strong working knowledge of AWS services, particularly S3.
• Proven ability to read, author, and troubleshoot complex JSON configurations.
• Proficiency in Python (or similar scripting language) for data processing and analysis tasks.
• Experience with ETL/ELT concepts and contributing to a modern data platform environment.
• Solid understanding of data modeling, data structures, and fundamental analytical/statistical methods.
• High attention to detail, commitment to data accuracy, and strong analytical and problem-solving skills.
• Fluent in written and spoken English.

Nice to Have

• Basic understanding of Kubernetes and containerized workloads.
• Familiarity with workflow orchestration tools such as Argo Workflows, Airflow, or similar.
• Experience supporting or troubleshooting production data pipelines.
• Experience with BI and data visualization tools (Superset, Metabase, Tableau, Looker, etc.).

What We Offer

• A collaborative environment where quality and engineering excellence are top priorities.
• The chance to work on products with real impact on a global creative community.
• Competitive salary and equity options.
• 50 work-from-home days annually.
• A fast-growing company with a flat structure and strong team culture.