Support Engineer : Allium

The 4 biggest blockchain strengths are also its weakness

• Permissionless nature leads to fragmentation of meaning
• Decentralization leads to too many standards
• Immutability leads to exponential data + query infrastructure complexity
• Neutrality means that no one is accountable for interpretations

Blockchain 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 standards
• Exponential complexity
• No accountability for interpretation
• Events without economic meaning

Finance cannot operate on that, it needs an effective system of record.

Allium is building the System of Record for Onchain Finance

Allium 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 income
• Standardization Gap: Mapping thousands of protocols into a single canonical cross chain schema
• Infrastructure Gap: Read optimized, globally distributed data at web scale
• Accountability Gap: Auditable methodology, SLAs, and SOC 1 and 2 compliance

The result is a neutral, canonical data layer institutions can build on with confidence.

Finance is moving onchain

Stablecoins, 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 Serve

Allium powers three core personas with the same canonical data foundation:

1. Finance, Accounting, and Risk Teams They 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.

What You’ll Learn

• How petabyte-scale data infrastructure works – Allium manages 5+ petabytes across every combination of cloud provider x data warehouse (Snowflake, BigQuery, Databricks…) x region. You’ll pick up how these systems are designed, where they break, and how to reason about freshness, cost, and correctness tradeoffs between them.
• How to build AI-native support – Tickets that feed runbooks; runbooks that support agentic skills; an agentic loop that builds on itself and compounds – You will learn how to build an AI-native support system that scales.
• How to manage expectations with institutional customers (banks, asset managers, exchanges, foundations) – What incident management best practices look like in production, how to communicate during a data incident, how to set an SLA you can actually keep, and how to thread the needle when two customers’ expectations conflict.
• How 100+ blockchains work under the hood – Resolving a ticket often means tracing a number back to raw on-chain data – why a stablecoin supply figure differs between two sources, why a balance snapshot lags, what a reorg does to a table. You’ll build genuine depth in EVM, Solana, and the long tail of chains.
• How enterprise data delivery works end to end – warehouse-native shares, APIs, Kafka streams, push vs pull. You’ll learn to pick the right mechanism for a customer’s problem, because half of support is knowing where in the product the answer already lives.
• How to run a data quality investigation – verification checks, cross-source reconciliation, and separating “the data is wrong” from “the query is wrong” from “the chain did something unusual.”
• A path into becoming an Allium Data Wizard, if that’s where you want to go. Every Wizard at Allium started on the frontlines; we believe staying close to customers and their use cases is how you learn the data best. This role builds exactly those skills: tracing numbers back to raw on-chain data, debugging SQL at scale, learning protocol mechanics.

What You’ll Do

• Troubleshoot and resolve complex customer issues involving SQL queries, data pipelines, API integrations and other Allium Integrations (e.g. kafka)
• Mapping customer issues to where the solution exists in Allium. Be it a table in the dataset, another delivery mechanism, relevant documentation, another integration pattern (e.g. push vs pull)
• Help customers diagnose problems in their data sources (Snowflake, BigQuery, Postgres, etc.) and optimize performance.
• Collaborate with engineering to investigate bugs, identify patterns, and ship fixes.
• Develop internal tools and scripts to automate troubleshooting and improve customer response times.
• Write clear documentation and knowledge base articles for customers and internal teams.
• Partner with the GTM and product teams to translate customer pain points into actionable insights.
• Participate in daily syncs to discuss ongoing issues, progress, and improvements.
• Synthesize all of the above into an AI-native system that builds leverage.
• Triage and prioritize incoming issues against customer SLAs — distinguishing a P1 data incident for an institutional customer from a routine query question, and sequencing your work so the highest-impact problems get resolved first.

What You’ll Bring

• Fluency in AI tools, common failure modes and modern practices.
• Fluency in SQL – you can confidently write, optimize, and debug complex queries.
• Experience providing technical support for a SaaS or data product.
• A working knowledge of blockchain data primitives across ecosystems like Solana and EVM chains.
• Familiarity with APIs, data connectors, and ETL tools.
• Comfort with scripting or automation in Python, Bash, or similar languages.
• Strong understanding of Linux environments and command-line tools.
• Excellent communication and documentation skills — you can explain complex concepts simply.
• A proactive, empathetic approach to customer relationships.
• The ability to work independently and take full ownership of issues from report to resolution.

Bonus Points

• Experience with data warehouses (Snowflake, BigQuery, Redshift) or BI tools.
• Exposure to infrastructure-as-code tools (Terraform, Ansible, etc.).
• Experience in debugging API or integration issues across cloud environments.
• Familiarity with data modeling or transformation frameworks (dbt, Airbyte, etc.).
• Experience with message queues and event buses (Google Pubsub, Kafka etc)