Senior Data Engineer

GoMining is an international crypto company that reshapes Bitcoin mining via its Liquid Bitcoin Hashrate (LBH) protocol. It creates Digital Miners, digital assets backed by real hashrate generating BTC rewards, and develops the LBH protocol for DeFi use and passive income. The company also offers Miner Wars, a Web3 Play-to-Earn strategy game integrating digital miners into the Web3 ecosystem. GoMining operates proprietary data centers and has over 3.7 million users worldwide, working on Ethereum, BNB Chain, and TON.

• 6+ years in Data Engineering with 3+ years at senior level.
• Strong software engineering background with excellent Python skills.
• Experience designing cloud-based data platforms and warehouses.
• Hands-on with Google Cloud Platform services: BigQuery, Dataflow, Pub/Sub, Composer (Airflow).
• Experience building ETL/ELT pipelines, streaming architectures, and API integrations.
• Experience with Terraform, Kubernetes, Docker, and CI/CD pipelines.
• Strong understanding of data modeling, distributed systems, and scalable architectures.
• Experience implementing data quality, monitoring, and observability solutions.
• Strong SQL skills.

Nice to have:

• Experience building ML infrastructure and supporting Data Science teams.
• Experience with Kafka or other streaming platforms.
• Experience in fintech, crypto, Web3, or high-scale B2C products.
• Experience with modern data lakehouse architectures.
• Experience using AI tools to improve engineering productivity.

Data Platform:

• Design and evolve cloud data platform on Google Cloud Platform.
• Develop scalable data architecture including Medallion Architecture.
• Define and maintain data models, contracts, and integration standards.

Data Engineering:

• Build and maintain batch and streaming data pipelines.
• Integrate data from internal services and third-party APIs.
• Develop ETL/ELT workflows and automate data processing.
• Build analytical data marts for business and product teams.

Platform Reliability:

• Ensure data quality, consistency, and reliability.
• Implement monitoring, alerting, and SLA management.
• Improve platform performance and scalability.

Engineering Excellence:

• Drive Infrastructure as Code (IaC), CI/CD, and automation.
• Contribute to ML and AI infrastructure development.
• Establish engineering best practices, code quality standards, and documentation.
• Collaborate with Analytics, Data Science, Product, and Engineering teams.