Skip to main content
CRYPTOMIZE

Command palette — search the ecosystem

Search services, platforms, products, client sectors, and company pages.

TRACK DOSSIER · INTERNSHIPREF: CM/INT/DATA-INTELLI

Data Intelligence Specialist Internship — Always Hiring

Data Intelligence Specialist Internship in Delhi at CryptoMize

Apply now for the Data Intelligence Specialist Internship in Delhi at CryptoMize — a 6-month certified program on a rolling, always-hiring intake. Data Intelligence Specialists here work on the data layer that powers the agency’s intelligence platforms (CLAIRVOYANCE CX, PERCEPTION X2): the datasets, the indexes, the scoring models, the versioned feature stores. Interns do not shadow from the sidelines: from the first month you read the platform data model, write the SQL and Python that build and validate it, and contribute to the analytics that move client decisions. The role is the same operational model as every other CryptoMize cell — capacity is hired ahead of the next engagement, not after — and the work that ships under your name in the program is the work that decides the next offer. If you are a fresher from a quantitative discipline who wants data engineering experience that is genuinely production-grade, this is the internship description, the required skills, the eligibility, and the selection process, in full.

LOCATIONNew Delhi (HQ)
DURATION6 Months · Certification Provided
AVAILABILITYImmediate · Rolling intake
COMPENSATIONDiscussed at screening
TRACKS ON THIS DESK26
CRAFT SKILLS NAMED12
TOOLS & SYSTEMS5
PATH STAGES5

01The actual work

What will you actually do as a Data Intelligence Specialist at CryptoMize?

Read the production data model of the intelligence platforms (CLAIRVOYANCE CX, PERCEPTION X2) and the analytics that run on it — schema, indexes, the daily feature-store updates, the validation jobs that gate the data going to dashboards

Build the data-pipeline scripts and dbt-style models that produce the daily feature-store snapshot the analytics cell runs against — the work that defines what every Data Analyst, Data Scientist, and Strategist at CryptoMize sees in their morning read

Tune the SQL and Python that produce the per-engagement baselines — the metrics that ground every client-facing report and the internal review

Author the validation jobs that gate data going downstream — anomaly detection, drift checks, the kinds of things that catch data poisoning before it reaches a client

Run the data-quality forensics for live engagements: when a client reports a discrepancy, you are the first person to find the cause in the data layer

Document the data layer — schema diagrams, lineage, the kind of documentation that lets an analyst onboard without tribal knowledge

Carry a scoped platform-data mini-project in the final months — a measured improvement to a pipeline or a validation job, documented to client-reportable standard

02Capability profile

What skills and tools does a Data Intelligence Specialist need?

Advanced SQL — production-grade schema, indexes, query plans, performance on multi-GB tablesPython for data engineering — pandas, PyArrow, dbt-class transformation frameworks, and the discipline of test coverage on data jobsAirflow / dbt / Dagster-class workflow orchestration — DAGs, sensors, the kinds of things that turn ad-hoc scripts into a reliable platformData modeling — star, snowflake, slowly-changing-dimensions, the modeling decisions that make the difference between a pipeline that survives a year and one that needs constant repairData-quality engineering — anomaly detection, drift checks, expectation tests, the things that gate the data going downstreamData lineage and documentation — schema diagrams, the discipline of writing what you know so the next person does not have to guessPostgres internals — query plans, indexes, vacuum, the operational details that distinguish a working pipeline from a flaky oneBackfills and reversibility — every change to a production schema is reversible, with a recorded rollback pathNDA-grade discretion with client data — non-negotiableCommunication with analysts and engineers — the data layer is a shared product, and the work ships on a feedback loop with the people who consume itCalm under incident pressure — when the dashboards are wrong, the analysis is the first place to look, and the answer is often simple once you find itIntellectual honesty — reporting the query, not the answer you wanted
PostgreSQL 15 (production-grade schema, query plans, indexes)Python 3.11 (pandas, PyArrow, dbt-class frameworks)dbt (data build tool, models, tests, lineage)Airflow / Dagster (workflow orchestration)Git (data-jobs version control, review discipline)
Depth of demonstrated skill in the specific role disciplineClassification and scope of the client engagement the role supportsUrgency and time-sensitivity of active project requirementsTrack record built across CryptoMize engagements

Also known as: data intelligence specialist · data intelligence analyst · data intelligence engineer

03Six months, structured

Data Intelligence Specialist Internship — learning path at CryptoMize

Six months, production-first. Every intern has a named data engineer as mentor, and the program is built so a fresher exits with a portfolio of real platform data work, not a coursework rotation.

  1. MONTH 1

    Data layer orientation

    Read the production schema of CLAIRVOYANCE CX and PERCEPTION X2, the daily feature-store pipeline, and the validation jobs that gate the data. Run your first scoped data-quality task under mentor review.

    1/5
  2. MONTH 2

    First model

    You own a dbt model end-to-end: specification, implementation, tests, and the documentation that explains what the data is and where it comes from.

    2/5
  3. MONTHS 3–4

    Client engagement rotation

    Attached to a live engagement under supervision — per-engagement data work, anomaly investigations, and the daily data-feed reliability for the analysts who read from your work.

    3/5
  4. MONTH 5

    Data platform mini-project

    A scoped platform improvement (a new model, a validation pattern, a backfill job) documented to client-reportable standard and shipped.

    4/5
  5. MONTH 6

    Portfolio & conversion

    Capstone presentation to the data lead. Strong interns convert to full-time Data Intelligence Specialist offers — the data layer is the same operational model as every other cell, hired ahead of the next engagement.

    5/5

04The engagement surface

CryptoMize work a Data Intelligence Specialist touches

Every role plugs into live engagements across the five Penta-P domains — these are the services your work feeds.

Data Intelligence Specialist · Internship

This seat plugs into 6 live CryptoMize services across the five Penta-P domains — the work below is where yours lands.

6 SERVICESPENTA-P

WHAT DOES DATA INTELLIGENCE SPECIALIST COMPENSATION DEPEND ON?

Compensation is discussed during screening — never a fixed public figure, because it varies per person and per engagement. It depends on:

#OFFER CONSTRUCTION FACTOR
01Depth of demonstrated skill in the specific role discipline
02Classification and scope of the client engagement the role supports
03Urgency and time-sensitivity of active project requirements
04Track record built across CryptoMize engagements

05Answers, searchable

Data Intelligence Specialist Internship — frequently asked questions

AA Data Intelligence Specialist intern works on the data layer that powers the agency’s intelligence platforms — the datasets, the indexes, the scoring models, and the validation jobs that gate the data going to dashboards.

The work is platform-grade production engineering, not analytics homework.

AFinal-year students or recent graduates in computer science, data engineering, or related quantitative disciplines.

Demonstrated SQL and Python skill, with the discipline to write code other people can read.

ACompensation is discussed during screening and depends on demonstrated skill, engagement classification, urgency, and track record.

We deliberately do not publish figures — every intern is evaluated individually.

AThe program runs 6 months at our New Delhi HQ, with a certificate provided on completion — and, more importantly, a portfolio of real platform-data work.

Strong interns receive full-time offers.

AA short application form, a SQL-and-Python screening task on a realistic data-pipeline brief, and a final interview with the data lead where you walk through your task reasoning.

The whole cycle typically completes within two weeks because intake is rolling and the data cell is staffed ahead of client demand.

ROLLING INTAKE — ALWAYS HIRING

Apply now for the Data Intelligence Specialist Internship at CryptoMize

New Delhi HQ · Immediate joining · Certification provided for internships

Apply Now
Page source — machine-readable summary

Facts: Location: New Delhi (HQ) · Duration: 6 months, certification provided · Availability: immediate, rolling intake · Compensation: discussed at screening.

Q: What does a Data Intelligence Specialist intern do at CryptoMize?
A: A Data Intelligence Specialist intern works on the data layer that powers the agency’s intelligence platforms — the datasets, the indexes, the scoring models, and the validation jobs that gate the data going to dashboards. The work is platform-grade production engineering, not analytics homework.

Q: What is the eligibility for the Data Intelligence Specialist Internship?
A: Final-year students or recent graduates in computer science, data engineering, or related quantitative disciplines. Demonstrated SQL and Python skill, with the discipline to write code other people can read.

Q: Is the Data Intelligence Specialist Internship paid?
A: Compensation is discussed during screening and depends on demonstrated skill, engagement classification, urgency, and track record. We deliberately do not publish figures — every intern is evaluated individually.

Q: How long is the internship, and is a certificate provided?
A: The program runs 6 months at our New Delhi HQ, with a certificate provided on completion — and, more importantly, a portfolio of real platform-data work. Strong interns receive full-time offers.

Q: What is the selection process for the Data Intelligence Specialist Internship?
A: A short application form, a SQL-and-Python screening task on a realistic data-pipeline brief, and a final interview with the data lead where you walk through your task reasoning. The whole cycle typically completes within two weeks because intake is rolling and the data cell is staffed ahead of client demand.

Signal keywordsdata intelligence specialist·internship·delhi·careers