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Blockchain Data Engineer

Patrick Durand

Freelance · Mid-level · New_York

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About the role

We operate a decentralised exchange protocol. $1.4 billion in total value locked, around $200 million in daily trading volume on busy days. We are incorporated, we have a legal team, we run structured engineering sprints, and we do not pay in governance tokens unless you want us to. We run like a normal software company, except our data infrastructure has some unusual properties. Every transaction is on-chain and public, but the raw chain data is not in a format that makes it easy to answer business questions quickly. We have an internal Databricks environment where we process raw chain events into cleaned, enriched tables that our analytics team and smart contract developers can query. The problem is that the pipelines that produce those tables were built by people who have since left, are inadequately documented, and have accumulated enough debt that adding a new chain integration or new contract type takes longer than it should. We are hiring a contract data engineer for a 12-week engagement to audit the existing pipeline architecture, refactor the highest-debt components, and document the system clearly enough that the next person who touches it can understand it without asking five people first. This is engineering work. It is not Web3 work specifically — if you know Databricks and ETL pipelines and are willing to learn the on-chain data model (it is not complicated), you can do this job.

Key Deliverables

List the expected deliverables for this project.

  • Audit the existing on-chain data pipeline architecture and produce a written assessment of debt, risk, and improvement priorities
  • Refactor the three highest-debt pipeline components: improve reliability, reduce processing time, and add adequate test coverage
  • Document the full pipeline: data sources, transformation logic, output schema, and operational runbook
  • Design and implement a standard for future pipeline additions so that new chain or contract integrations follow a consistent, documented pattern
  • Hand off to the internal team with a structured knowledge transfer session at the end of the engagement

Requirements

Technical stack needed for this mission.

  • 4+ years of data engineering with strong pipeline architecture and refactoring experience
  • Databricks — Delta Lake, structured streaming, and job orchestration at production scale
  • Python for pipeline logic, data transformation, and tooling
  • SQL for data modelling, validation queries, and analytical layer design
  • ETL pipeline design: schema evolution, idempotency, incremental processing, and failure recovery
  • Kafka or equivalent streaming experience for processing high-volume event data
  • No blockchain experience required — willingness to read documentation and ask questions is sufficient

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Contract Type

Fixed-price

Level

Mid-level

Budget Range

$22,000 / 12 weeks

Duration

12 weeks

AI Expertise

MLOps & AI Infrastructure

Skills

python sql etl databricks kafka

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