Data Engineer jobs in Delhi at CryptoMize are open on a rolling, always-hiring basis — the pipeline layer feeding forecasting and analytics at engagement scale is permanent infrastructure and we staff it ahead of demand. This is a full time, permanent position with immediate joining at our New Delhi HQ, owning the ingestion and transformation backbone that moves OSINT harvests, sentiment corpora, electoral data, and media flows into the modeled tables our analysts and models query. The complete job description follows: responsibilities, requirements, seniority path, and selection process. Engineers who believe correctness is a personality trait — welcome home. The pipeline layer moves OSINT harvests, sentiment corpora, electoral data, and media flows at engagement scale, and every forecasting model the organization ships is exactly as trustworthy as the data you hand it.

LOCATION New Delhi (HQ)

EMPLOYMENT Full-time · Permanent

AVAILABILITY Immediate · Rolling intake

COMPENSATION Discussed at screening

TRACKS ON THIS DESK6

CRAFT SKILLS NAMED12

TOOLS & SYSTEMS4

PATH STAGES4

01 01The actual work What will you actually do as a Data Engineer at CryptoMize? 01 Own pipeline domains end-to-end — ingestion, transformation, orchestration, and the on-call honesty that keeps them trustworthy 02 Design and evolve the data model our analytics and forecasting layers query: star-schema discipline, idempotent loads, incremental patterns 03 Build data-quality engineering as infrastructure — validation gates, poisoning detection, and anomaly alerting an intelligence shop actually needs 04 Operate orchestration at production scale: dependency chains, backfills, and failure handling that recovers without human archaeology 05 Own pipeline performance: noticing the slow transformation before the analyst does, and fixing it without breaking correctness 06 Set the operability standard — runbooks, monitoring, and documentation so any engineer can operate any pipeline 07 Sit at the foundation of an 89%-accuracy forecasting operation across 18 countries: every model is exactly as trustworthy as what we hand it 08 Contribute to the platform’s standards themselves — the review rubrics, runbook templates,



and quality-gate patterns every pipeline inherits ROLE RESPONSIBILITIES As a Data Engineer at CryptoMize you will design, build, and operate the pipelines that move engagement data from raw arrival to modeled, queryable tables — applying idempotent load patterns, validation gates, and orchestration discipline so the layer runs without heroics. The forecasting operation downstream is exactly as accurate as the data you hand it, which makes correctness a client-facing responsibility. Standing duties include data-quality engineering and observability: poisoning detection for adversarial inputs, drift alerts for quietly changing sources, and the monitoring posture that surfaces a failing pipeline upstream of the analyst who would otherwise discover it. In an intelligence organization, hostile data is not hypothetical. Engineers here also carry the operability standard: runbooks maintained as living documents, code reviewed as a matter of course, and intern pipelines mentored to the same bar. The platform compounds only where its engineers teach. 02 02Capability profile What skills and tools does a Data Engineer need? astro-island,astro-slot,astro-static-slot{display:contents} Craft skills12 Tools & systems4 Offer standards4 Expert SQL — transformation architecture, window functions, incremental/idempotent load designProduction Python — pipeline code reviewed, tested, and operable by othersData modeling at scale — dimensional design and evolution without breaking downstreamOrchestration mastery — scheduling, backfills, dependency graphs, failure recoveryData-quality engineering — validation gates, drift detection, poisoning defenseAPI ingestion at scale — rate limits, pagination, schema drift, hostile sourcesPerformance engineering — query planning, partitioning, load strategyInfrastructure fluency — Linux,



containerized pipeline deploymentObservability — pipeline monitoring that catches issues upstream of the analystRunbook and documentation disciplineMentorship of pipeline interns and junior engineersConfidentiality at NDA grade (non-negotiable) PostgreSQL 15 at production scalePython 3.11 pipeline toolchaindbt-style transformation layeringAirflow-class orchestration + containerized deployment 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 warehouse engineer · pipeline engineer · ETL developer · platform data engineer 03 03Seniority ladder Data Engineer — seniority path at CryptoMize Engineers advance by the reliability of the pipelines they run and the correctness culture they enforce. Data Engineer Owns pipeline domains — the ingestion and transformation backbone analysts depend on daily. 1/4 Senior Data Engineer Designs the data architecture, leads quality engineering, and owns the hardest pipeline surfaces. 2/4 Data Platform Lead Carries the platform itself — standards, tooling, staffing, and the reliability contract with analytics. 3/4 Infrastructure crossover The track into broader platform and security infrastructure — engineers whose systems depth becomes architectural authority. 4/4 04 04The engagement surface CryptoMize work a Data Engineer touches Every role plugs into live engagements across the five Penta-P domains — these are the services your work feeds. Data Engineer · Job Opening This seat plugs into 5 live CryptoMize services across the five Penta-P domains — the work below is where yours lands. 5 SERVICESPENTA-P Big Data Mining OSINT Sentiment Analysis Predictive Intelligence Data Recovery WHAT DOES DATA ENGINEER 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 01 Depth of demonstrated skill in the specific role discipline 02 Classification and scope of the client engagement the role supports 03 Urgency and time-sensitivity of active project requirements 04 Track record built across CryptoMize engagements

📌 Data Engineer (India)
🏢 Crypto Mize
📍 India