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Inseego

Data Analytics Engineer

  • Seen live on Inseego's site today
  • Mid level
Pay
Not stated
Location
Bengaluru, India
Open for
12+ days
First seen
Oct 23, 2026
Apply on Inseego's site (opens in a new tab)

Posting record

No flags

Open 12+ days

The posting's record, oldest first
  1. Inseego's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Inseego, so its true age is longer.

Last checked Nov 4, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

Inseego is a global leader in wireless broadband, delivering fast, reliable connectivity to homes, businesses, and people on the move. With the acquisition of Nokia’s FastMile fixed wireless access product, Inseego offers one of the industry’s broadest cellular broadband portfolios, spanning fixed wireless gateways, mobile hotspots and routers, enterprise and industrial gateways, and cloud-based device, network, and subscriber management software. Backed by decades of wireless engineering expertise across 5G, Wi-Fi, antenna design, and cloud software, Inseego partners with mobile network operators worldwide to deliver connectivity at scale. Headquartered in San Diego, California, Inseego has offices in Amsterdam, Bangalore, and Athens.

Preferred Qualifications

  • Microsoft Fabric certification (DP-600 or equivalent) or Azure Data Engineer Associate (DP-203)
  • Direct experience with Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, Direct Lake)
  • Experience extracting data from Oracle NetSuite (ODBC, SuiteAnalytics Connect, REST API, or CSV exports)
  • Experience with Salesforce data extraction (Bulk API, Tableau CRM, or CRM Analytics)
  • Familiarity with dbt (data build tool) for SQL-based transformation layer
  • Knowledge of Delta Lake / Apache Parquet file formats
  • Experience with Informatica or Celigo as upstream integration/data sources
  • Exposure to Rippling or Arena data structures for HR and product data analytics Technical Stack & Tools
  • Analytics Platform: Microsoft Fabric (OneLake, Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2)
  • Visualization: Power BI (Direct Lake, semantic models, DAX)
  • ERP Source: Oracle NetSuite (SuiteAnalytics Connect / REST API)
  • CRM Source: Salesforce (Bulk API / connected app)
  • HRIS Source: Rippling
  • PLM Source: Arena • Integration Layer: Informatica / maybe move to Celigo(upstream data provider)
  • Languages: SQL (T-SQL / Spark SQL), Python / PySpark, DAX
  • Storage: Delta Lake / OneLake (Parquet)
  • Optional: dbt for transformation layer

Preferred Qualifications

  • Microsoft Fabric certification (DP-600 or equivalent) or Azure Data Engineer Associate (DP-203)
  • Direct experience with Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, Direct Lake)
  • Experience extracting data from Oracle NetSuite (ODBC, SuiteAnalytics Connect, REST API, or CSV exports)
  • Experience with Salesforce data extraction (Bulk API, Tableau CRM, or CRM Analytics)
  • Familiarity with dbt (data build tool) for SQL-based transformation layer
  • Knowledge of Delta Lake / Apache Parquet file formats
  • Experience with Informatica or Celigo as upstream integration/data sources
  • Exposure to Rippling or Arena data structures for HR and product data analytics

Technical Stack & Tools

  • Analytics Platform: Microsoft Fabric (OneLake, Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2)
  • Visualization: Power BI (Direct Lake, semantic models, DAX)
  • ERP Source: Oracle NetSuite (SuiteAnalytics Connect / REST API)
  • CRM Source: Salesforce (Bulk API / connected app)
  • HRIS Source: Rippling
  • PLM Source: Arena
  • Integration Layer: Informatica / maybe move to Celigo(upstream data provider)
  • Languages: SQL (T-SQL / Spark SQL), Python / PySpark, DAX
  • Storage: Delta Lake / OneLake (Parquet)
  • Optional: dbt for transformation layer

Education

  • Bachelor in Electronic and Communication or related degree

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