Head of Data Engineering

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Block Labs

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Crypto • Web 3 • B2B

Block Labs is a Web3-focused builder, investor, and marketing partner for blockchain projects. The company provides end-to-end blockchain development (smart contracts, decentralized wallets, NFT exchanges, payment gateways), web3-native marketing (social management, influencer/KOL campaigns, paid media, PR, partnerships), and investment support from seed to Series A. Block Labs works with founders to accelerate growth through technical development, go-to-market strategies, and strategic capital, operating from Sofia, Bulgaria.

51 - 200 employees

Founded 2022

₿ Crypto

🌐 Web 3

🤝 B2B

📋 Description

• Set the direction for our data platform, covering ingestion, transformation, warehousing and governance. • Build and lead a strong data engineering team capable of supporting both real time and batch workloads. • Design data architectures that serve multiple products, including AI models, real time scoring systems and analytical tools. • Establish clear data standards, schemas and contracts so teams can integrate with confidence. • Put in place robust data quality checks, validation steps and reconciliation processes to ensure information is accurate and consistent. • Work closely with AI teams to provide reliable feature pipelines and training data, and to support inference workflows. • Collaborate with backend and platform teams to integrate event streams, APIs and operational data into the platform. • Implement proper observability across the data stack, including lineage, freshness, completeness and performance. • Make informed decisions on tooling across storage, orchestration, streaming, and transformation. • Oversee documentation and architectural guidelines to keep the platform coherent as it grows. • Support product and partner teams when data from casinos or external systems needs to be integrated. • Maintain awareness of infrastructure costs and design choices that keep the platform sustainable in the long run.

🎯 Requirements

• Strong experience leading data engineering teams and delivering production data platforms that support real products, not just dashboards. • Comfortable designing and operating data pipelines and warehouses that serve both operational systems and analytical or modelling needs. • Good understanding of streaming technologies, batch processing and cloud native data tooling. • Practical experience working with machine learning teams or directly with ML pipelines, including feature generation, training data preparation and model serving. • Familiar with ML operations in a real setting, such as monitoring model inputs and outputs, handling data drift, and keeping training and production environments in sync. • Hands on experience with workflow orchestrators such as Temporal, Airflow or Dagster, ideally across both data and ML workflows. • Deep knowledge of SQL and at least one modern data processing engine or framework. • Comfortable with tools that support data quality, lineage, metadata and observability across both data and model pipelines. • Able to work closely with AI, backend, product and analytics teams and explain technical decisions in clear language. • Confident in architectural decision making, setting standards, and mentoring engineers at different levels. • Someone who cares about clarity, reliability and thoughtful engineering, and who understands the trade-offs between speed, cost and long-term maintainability.

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development