Blockchain Data Analyst

The 4 biggest blockchain strengths are also its weaknessPermissionless nature leads to fragmentation of meaningDecentralization leads to too many standardsImmutability leads to exponential data + query infrastructure complexityNeutrality means that no one is accountable for interpretationsBlockchain data is public. It is not usable at institutional scale. Despite being open, blockchain data is fragmented, hard to interpret, and painful to maintain. Even a simple question like “Who are the largest Ethereum token holders over time?” can require running nodes, ingesting full chain history, decoding contracts, cleaning edge cases, and writing complex SQL.Blockchains are optimized for writes, not reads.They are built for consensus and execution, not searchability, standardization, or financial interpretation. Blockchains are computers, not databases. Every protocol defines its own schema. The same economic action can be encoded in dozens of different ways. The result:Fragmented standardsExponential complexityNo accountability for interpretationEvents without economic meaningFinance cannot operate on that, it needs an effective system of record.Allium is building the System of Record for Onchain FinanceAllium ingests, verifies, and standardizes data across 140+ blockchains and 30+ petabytes of history. We close four structural gaps that prevent blockchains from becoming systems of record:Semantic Gap: Translating raw events into financial concepts like payments, trades, deposits, and staking incomeStandardization Gap: Mapping thousands of protocols into a single canonical cross chain schemaInfrastructure Gap: Read optimized, globally distributed data at web scaleAccountability Gap: Auditable methodology, SLAs, and SOC 1 and 2 complianceThe result is a neutral, canonical data layer institutions can build on with confidence.Finance is moving onchainStablecoins, tokenized assets, trading, staking, and lending are growing rapidly. Institutions need a trusted source of truth for onchain financial activity, just as they rely on Bloomberg or DTCC in traditional markets. Raw blockchains cannot serve that role.As AI agents begin transacting autonomously, the requirement becomes even stricter. Agents cannot reason over raw event logs. They need structured data, attribution, condition checks, and auditability.Allium is the read layer that makes onchain finance usable for humans and machines.Who We ServeAllium powers three core personas with the same canonical data foundation:1. Finance, Accounting, and Risk TeamsThey need reliable, audit grade answers. They rely on Allium for financial reporting, reconciliation, compliance, risk monitoring, and defensible metrics that can stand up to auditors and regulators.2. Engineers and Product Teams They need low latency, production ready infrastructure. They use Allium to power wallets, trading systems, payment rails, staking infrastructure, and real time applications that cannot break.3. Strategy, Research, and Executive Teams They need clarity and insight. They use Allium to understand ecosystem economics, market structure, user behavior, competitive dynamics, and where capital is flowing onchain.and of course.. agents 🦞. Our customers and users include Visa, Stripe, G-SIB Banks, Big 4 Accounting firms, BCG, Coinbase, Phantom, Uniswap and cited by the Federal Reserve.About the roleAt Allium, Blockchain Data Wizards are the data architects who transform raw, fragmented on-chain data into elegant, meaningful abstractions that power the world's largest crypto applications.You'll be equal parts detective, data engineer, and protocol researcher—diving deep into blockchain internals, reverse engineering DeFi protocols, and crafting data models that institutions and developers rely on.What you will doCreating Meaningful Data AbstractionsTransform messy on-chain data into unified, intuitive data models (e.g dex.trades, lending.liquidations) that work across verticals and protocols, providing users with granular, reliable insights.Reverse Engineer DeFi Protocol MechanicsDive deep into the mechanics of new DeFi protocols, dissect smart contract interactions and on-chain events, extract the data that matters, and transform it into clean, production-ready models using SQL/dbt.Indexing New BlockchainsDive into a blockchain’s raw data structures, ensure complete and accurate data capture, and design schemas that translate native blockchain data into reliable internal models, becoming the trusted source of truth for that ecosystem.Building Metrics & Filtering NoiseDesign and create metrics people can actually use - volumes, fees, TVL, and user activity, and filter out noise like wash trades, bots, and Sybil attacks. Make it easy for the industry to see what’s real and what matters.QualitiesSherlock & Enola Holmes-Level CuriosityYou find peculiarities in data that others miss. You question assumptions, dig deeper when something looks off, and help the industry redefine narratives with evidence-based insights.Product-Minded Data DesignYou don't just build tables—you design data products. You think about query patterns, performance, documentation, and how end users will interact with your models.Comfortable with AmbiguityNew blockchains and protocols have sparse documentation. You thrive when you need to figure things out yourself through exploration and experimentation.SQL/dbt MasteryYou can write elegant, performant SQL transformations that process large volumes of data. You understand incremental models, macros, and how to build maintainable data pipelines at scale.