Associate 2 – GTS Engineer (Azure Data Engineering)

KPMG — Bengaluru, Karnataka

₹3–7 LPA (HireSetu estimate) · 0–3 yrs exp · Freshers eligible · Full-time · onsite · Apply by 29 Nov 2026

HireSetu listing reference 28a703 — confirm requirements below, then apply on the employer site.

Quick answer: An entry-level Azure data engineering role whose output goes to audit and financial analytics teams, not to a product. The intake is narrow: BE/B.Tech/MCA from IITs or schools like NMIMS, with 0-3 years allowed.

From KPMG's job posting

Roles & responsibilities

The Azure Data Engineer in GTS - DES is an entry-level position for fresh graduates from premium Engineering institutes. Individual will join the GDC Technology Solutions (GTS) team, supporting the Clients in Data & Analytics Audit/ Financial domain. This role is designed for individuals eager to learn and develop foundational skills in ETL, building data pipelines, Data Engineering Services on Azure cloud platform

Assist in data extraction, transformation, and loading (ETL) using Azure Data Factory and Databricks under senior support

Support the development and maintenance of Python/PySpark notebooks for basic business logic.

Help integrate data from ERP systems (SAP, Oracle, Microsoft Dynamics) into Azure-based workflows

Support Audit teams on Financial D&A and insights using multiple technologies

Support clients with medium complexity and data size and strive to pick up complex clients

Assist Audit engagement teams in data extraction process by coordinating with the Client’s IT teams and other technical leads

ETL Services (SAP/Oracle/Microsoft Dynamics or others) systems into the KPMG proprietary tool and understand the data from functional and technical perspectives to resolve issues that arise while processing the data

Develop proficient understanding of D&A tools and capabilities with a focus on one or two sub-modules such as Journal entry testing, Sub-ledger analysis around O2C, P2P etc.

Strive to contribute to resolution of basic issues under the guidance of the Seniors

Development

Designs, codes, verifies, tests, documents, amends, and refactors simple programs/scripts. Applies agreed standards and tools, to achieve a well-engineered result. Reviews own work

Assist in development of operational and/or engagement team related routines in the chosen technology

Assist in practice development initiatives.

Good/ working experience of below technologies

Azure, Data Bricks, PySpark, SQL Server, Power BI,

Visualization tools Power BI Desktop

Programming skills on Python or any other programming software

Good understanding on Gen AI and working experience is preferred

Qualifications

This role is for you if you have the below

Educational qualifications

BE/B.Tech/MCA from Premium institutes like IITs and Dual degree (B.Tech+ MBA) from IITs, NMIMS etc.

Work experience

0-3 years

Text from KPMG's official job posting, formatted by HireSetu. The employer's own page is the final word on details.

HireSetu's note

The institute list is a real filter

KPMG names IITs, dual degrees and NMIMS for a 0-3 year opening. That is a tight intake for an entry-level data job, and the shortlist leans on campus and tier-one pipelines. A BE/B.Tech/MCA from elsewhere can still apply, but read the odds honestly. The work is onsite in Bengaluru and full-time, so plan around a regular office routine rather than travel or client-site stints.

Your customer is the audit team

You pull data out of SAP, Oracle or Microsoft Dynamics into Azure, build the pipelines, and hand results to auditors running journal entry testing and sub-ledger work around O2C and P2P. Good here means data that ties back to the ledger, row for row, and a pipeline that survives a messy client extract. Someone chasing petabyte-scale platform engineering will find this narrow. Someone curious about how finance data actually behaves will like it.

Revise SQL and the money flow

SQL to a working level: joins, grouping, window functions. Then PySpark notebooks, how ADF pipelines and Databricks jobs fit together, star schema and RDBMS basics, Power BI, and what SSIS and SSAS packages are for. The functional side matters as much. Learn how money moves through a business: order to cash, procure to pay, what sits in a journal entry, why a sub-ledger exists next to the general ledger. Knowing where SAP stores financial postings, BKPF and BSEG being the usual starting tables, will help you follow conversations in your first weeks.

Two years in, two directions

You can go deeper into data engineering: ADF, Databricks, PySpark, cloud data platforms. Or you move toward audit analytics, becoming the person who holds both the finance question and the data. The listing asks you to pick one or two sub-modules and learn them well, so specialisation starts early. Gen AI appears as a preferred skill, and being able to say where it fits in a data pipeline is useful here.

Drafted with AI from KPMG's job posting and checked by Prashanth Jakkula before publishing. See our Editorial Policy.

How to apply

  1. Open KPMG's careers site with the Apply button.
  2. Enter your email address; Oracle sends a one-time code instead of asking for a password.
  3. Upload your resume or fill in the profile form, then answer the questions for this role.
  4. Submit and keep the confirmation email, which also lets you track the application.

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