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What an information architect
really does.

20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.

20evidenced tasks

67,140in the US (2025)

$139,500median pay / year

9systems it runs on

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Create data models and schemas

Design canonical entity and relationship schemas for the customer, pro…4 sources agree

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The work, task by task

20 tasks

Hands on the work16

Create data models and schemas+

Design canonical entity and relationship schemas for the customer, product, order, and inventory domains; include field types, cardinality, validation rules, and sample JSON and CSV exports for the API team to consume by Thursday.

escojdonetwiki4 agree

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Optimize database performance+

Profile current query runtimes and index usage for the orders and analytics databases, propose index and partition changes that cut 95th-percentile response time by half, and produce a change plan for the DBAs to apply during the 02:00 maintenance window.

jdonet2 agree

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Express strategic data requirements+

Write a two-page strategic brief that maps business goals to measurable data capabilities: authoritative customer record, realtime product availability, unified reporting, and the timelines and data owners required to deliver each capability this fiscal year.

jdwiki2 agree

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Implement data backup and recovery procedures+

Document and configure nightly full and incremental backups for the customer and transaction datasets, define RTO and RPO for each, and validate recovery by restoring last week's backup into isolated test environment before Friday.

jdonet2 agree

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Create and manage data models+

Update the canonical data model for contacts and accounts, normalise redundant fields, publish the model with attribute-level definitions and sample mappings, and notify integration owners to reconcile within two sprints.

jdonet2 agree

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Perform data analysis+

Analyse the customer transaction and product feed logs for Q2 to spot missing fields, inconsistent identifiers, and outliers, produce a cleaned CSV with column definitions and a short data-quality memo for the analytics team by Wednesday noon.

esco

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Create data sets+

Assemble canonical customer and product tables from the CRM export and the storefront feeds, normalise identifiers, add provenance columns, sample-check 500 rows, and deliver two ready-to-load datasets plus a schema document by Friday.

esco

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Provide technical guidance to team members+

Write a short technical note for the API and frontend teams explaining the agreed JSON schema, required field validation rules, and two example payloads they can use to test integration by Tuesday morning so engineers can start client work on Wednesday.

jdonet2 agree

when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

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What the work runs on

named inside the evidenced tasks

4 tasksApache Hivesupports defining analytical data requirements and schemas for batch processing and reporting across the data lake that the strategy will target

4 tasksApache Hadoophandles bulk data migrations and staged testing against large sanitized datasets during development and validation of schema changes

3 tasksApache Cassandramodels distributed wide-column schemas and supports schema design for high-volume transactional data that an information architect maps out

3 tasksApache Airfloworchestrates data workflows and ensures model publication and downstream reconciliation jobs run on a schedule tied to governance activities

2 tasksAmazon Redshiftprovides analytics workload profiling and helps design distribution and sort keys to optimize complex queries

2 tasksAmazon Web Services AWSprovides the cloud storage, snapshot, and recovery orchestration services needed to define and validate backup and restore procedures

2 tasksAJAXused for web programming and client-server integration tasks relevant to API and frontend testing

1 taskAdobe Acrobatused to produce and distribute the training handout and FAQ as a professional, printable document

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Can AI actually do this job?

the honest answer

It can

where it genuinely helps

Explain the theory behind the work
Draft, tidy and structure your writing
Rehearse a hard conversation before you have it
Build a study plan that fits your gaps

It cannot

where it stops, completely

Be in the room where an information architect actually works
Carry the responsibility when the call is wrong — that weight stays yours
Notice what no one wrote down: the hesitation, the thing left unsaid
Live with the outcome

What the work pays

two countries, two different measures

United States

this exact occupation · BLS 2025

$139,500 a year — the middle: half earn more, half earn less
The lowest tenth earn near $86,240; the top tenth near $204,000
67,140 people employed in this occupation

India

the occupation GROUP, not this job · PLFS via ILOSTAT 2025

₹38,298 a month — the median for Professionals, the group this work sits in
India publishes pay by broad occupation group, so this covers many jobs besides this one. It is a shape, not a salary.

read this carefullyThese two numbers are not comparable and must not be converted into each other. One is a yearly figure for this job alone; the other is a monthly figure for a whole family of jobs. What travels between them is the pattern, not the amount: experience lifts pay almost everywhere.

Where the evidence lives

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O*NETThe US Department of Labor's own record of this job9 of these tasks ESCOThe European skills and occupations register5 of these tasks Job descriptionsReal postings, in the wild11 of these tasks WikipediaHow the world describes this work5 of these tasks US Bureau of Labor StatisticsPay and employment, by occupation2025 figures UK NOS ASTBUS410Create and manage information systemsnational standard UK NOS TECDT80851Design data processing systemsnational standard

Close to this work

12 nearby

Library ScienceLibrary Technician24 evidenced tasks Library ScienceArchivist Aide24 evidenced tasks Library ScienceLibrary Assistant23 evidenced tasks Library ScienceInformation Literacy Instructor21 evidenced tasks Library ScienceRecords Clerk20 evidenced tasks Library ScienceDocument Controller20 evidenced tasks Library ScienceAssistant Librarian20 evidenced tasks Library ScienceInformation Scientist20 evidenced tasks

Questions people actually ask

You spend the morning meeting developers and analysts to agree data needs and review schemas, then map that to storage choices like Amazon Redshift or Cassandra.

Afternoons are hands-on: editing data models, testing schema changes in a staging cluster (AWS EC2), running Airflow jobs, and troubleshooting data integrity or performance issues. Evenings often include writing documentation, a common business vocabulary, or answering user questions.

Start with Amazon Web Services (AWS) essentials—EC2 for instances and Redshift for analytical warehousing—because many companies use them.

Learn one NoSQL system like Apache Cassandra and a Hadoop ecosystem tool such as Apache Hive or HDFS; add Apache Airflow for orchestration. Knowing how these work together helps you design storage and backups.

A data engineer builds ETL pipelines and code (writing Airflow DAGs, web programming for AJAX APIs), focusing on moving data. An information architect defines how data is stored, the schemas, and the business vocabulary you all follow.

Architects design models and standards, estimate project time/cost, and set database parameters; engineers implement and optimize those designs.

Yes, but treat AI output as a draft. Use AI to generate example ER diagrams, column names, or vocabulary suggestions, then validate against your constraints, performance needs, and security rules.

Never let AI alone change production schemas or credentials. Have a human review, test changes in staging (EC2 or a test Redshift cluster), and record decisions in your documentation.

The U.S. Bureau of Labor Statistics reports 67,140 people in this SOC with a median wage of $139,500 per year; the lowest tenth earn $86,240 and the top tenth earn $204,000. (Source: BLS, 2025.)

Actual offers vary by city, employer, and experience. Cloud and big-data skills (Redshift, Cassandra, Hadoop, Airflow) push pay toward the higher end.

Learning to create and test clear data models and schemas improves everything: it reduces developer confusion, prevents integrity errors, and makes backups and recovery predictable.

Practically, that means getting comfortable modeling in the tools your team uses (Redshift table design, Cassandra partition keys, Hive schemas), then testing performance and recovery in a staging environment.