Data Analytics Engineer

Bengaluru, India

Live, first seen by us 24 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: SALARIED_FT
From the employer’s posting

What you’ll work on

Full posting

Build data pipelines into Microsoft Fabric (Lakehouse, Warehouse, Pipelines)
Extract data from Oracle NetSuite and Salesforce for analytics
Develop Power BI semantic models and reports using Direct Lake and DAX
Write SQL, Python and PySpark transformations on Delta Lake / OneLake storage

From the employer’s posting

Analytics Platform: Microsoft Fabric (OneLake, Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2)

ERP Source: Oracle NetSuite (SuiteAnalytics Connect / REST API)

Visualization: Power BI (Direct Lake, semantic models, DAX)

Languages: SQL (T-SQL / Spark SQL), Python / PySpark, DAX

What you’ll bring

All qualifications

Core experience

Experience with Microsoft Fabric (OneLake, Lakehouse, Pipelines, Dataflows Gen2)
Proficiency in SQL (T-SQL / Spark SQL) and Python / PySpark
Power BI with DAX and semantic models

Preferred experience

Experience extracting data from Oracle NetSuite (ODBC, SuiteAnalytics Connect, REST API, or CSV exports)
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)
Experience with Salesforce data extraction (Bulk API, Tableau CRM, or CRM Analytics)

Qualification wording

Direct experience with Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, Direct Lake)

Languages: SQL (T-SQL / Spark SQL), Python / PySpark, DAX

Visualization: Power BI (Direct Lake, semantic models, DAX)

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)

Apply at Inseego

Posting record

Report an error

Status in our records: Live
First seen by us: Oct 11, 202624 days ago
Recorded sightings: 21
Last seen by us: Nov 4, 2026
Employer says posted: Oct 8, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 24

Similar jobs usually come down between day 6 and day 47.

From 1,417 similar postings that came down. Coming down is not always a hire.

Inseego is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
Azure
dbt
Delta Lake
Oracle
Power BI
Spark
Tableau
PySpark

Where the posting names them

- 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)

- Integration Layer: Informatica / maybe move to Celigo(upstream data provider) - Languages: SQL (T-SQL / Spark SQL), Python / PySpark, DAX - Storage: Delta Lake / OneLake (Parquet)

- 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

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)

- Storage: Delta Lake / OneLake (Parquet) - Optional: dbt for transformation layer Preferred Qualifications :

- Storage: Delta Lake / OneLake (Parquet) - Optional: dbt for transformation layer Education:

- 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

- Languages: SQL (T-SQL / Spark SQL), Python / PySpark, DAX - Storage: Delta Lake / OneLake (Parquet) - Optional: dbt for transformation layer

- 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)

- Visualization: Power BI (Direct Lake, semantic models, DAX) - ERP Source: Oracle NetSuite (SuiteAnalytics Connect / REST API) - CRM Source: Salesforce (Bulk API / connected app)

- 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)

- 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

Upload resume Add LinkedIn

Your next step

Complete your application on ats.rippling.com. The employer’s form will show what is required.

Applying through Rippling

“The résumé will be parsed to fill in the application details”: check what it filled before you send.

Already applied? Track this application

About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern