Data Engineer

About the role

We are seeking a Data Engineer to join our Data Engineering team and support Wirestock's data infrastructure. This role involves building, optimizing, and maintaining scalable data pipelines and a structured data ecosystem. You will transform raw data into actionable intelligence, analyze large‑scale datasets, and generate insights for 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.
• Contribute to the design, optimization, and documentation of ETL/ELT pipelines and data governance processes.

Required profile

• 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.
• Experience with ETL/ELT concepts and modern data platform environments.
• Solid understanding of data modeling, data structures, and fundamental analytical/statistical methods.
• Fluent in written and spoken English.

Required skills

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

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.