D365 Customer Insight Data Engineer

DysrupIT

Data Engineer managing D365 Customer Insights and data pipelines. Triage issues, validate data fitness, and collaborate on monitoring and observations.

Posted 6/5/2026full-timeRemote • 🇮🇳 IndiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

Azure.NETPythonSQL

About the role

Key responsibilities & impact

D365 CID administration & support
Support and extend an existing CID setup onboard new sources, tune unification rules, manage refresh schedules and environment configuration.
Triage and resolve CID issues raised by the customer’s business and IT teams: failed refreshes, broken segments, profile-count discrepancies, export failures, permission issues.
Manage Support tickets with Microsoft relating to CID issues.
Operate and support upstream data pipelines feeding CID.
Validate data on date and data fitness for CID (schema, keys, types, nulls, duplicates) — and fix or escalate when it isn’t.
Build and maintain monitoring on pipeline runs, refresh status, row counts, and SLAs.
Perform root-cause analysis end-to-end — source → lake → pipeline → CID → consumer — and produce clean write-ups and permanent fixes, not just patches.
Run regular service reviews with the customer’s data and CRM stakeholders, log changes through formal change control, and keep documentation current.

Requirements

What you’ll need

3–6 years in a data engineering, data operations, or BI/analytics engineering role.
Hands-on production experience with Dynamics 365 Customer Insights — Data (formerly Customer Insights / CDP): data sources, unification, segments, measures, exports, environment administration.
Strong Azure Data Lake Storage Gen2 experience — folder structures, CDM folders, Delta / Parquet, access control, ingestion patterns.
Practical ability to read, debug, and modify .NET / C# console applications that orchestrate data pipelines — enough to triage failures, fix logic bugs, and ship small enhancements.
Solid SQL and data modelling fundamentals; comfortable with large data volumes and performance troubleshooting.
Disciplined incident management — clean tickets, clear comms, structured root-cause analysis.
Exposure to Microsoft Fabric (Lakehouse, OneLake, Dataflows Gen2, Notebooks, Pipelines) is strongly preferred.
Python for data wrangling and notebook work.
Experience supporting customers across multiple time zones (AU and/or Middle East a plus).

Benefits

Comp & perks

Professional development opportunities

ATS Keywords

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Hard Skills & Tools

D365 CID administrationdata engineeringdata operationsBI engineeringAzure Data Lake Storage Gen2SQL.NETC#Pythondata modeling

Soft Skills

incident managementroot-cause analysiscommunicationdocumentation