Job Description

About Sonata Software

In today's market, we observe a distinct duality in technology adoption. On one front, clients are keenly focused on cost containment, while on the other, there is a strong drive to modernize their digital storefronts, aiming to appeal to both consumers and B2B customers alike. As a leading Modernization Engineering company, we aim to deliver modernization-driven hypergrowth for our clients based on the deep differentiation we have created in Modernization Engineering, powered by our Lightening suite and 16-step Platformation playbook. In addition, we bring agility and systems thinking to accelerate time to market for our clients.Headquartered in Bengaluru, India, Sonata Software has a strong global presence, with strategic operations spanning across key regions such as the US, UK, Europe, APAC, and ANZ. We are a trusted partner of world-leading companies in TMT (Telecom, Media, and Technology), Retail & CPG, Manufacturing, BFSI (Banking, Financial Services and Insurance), and HLS (Healthcare and Lifesciences). Our bouquet of Modernization Engineering services cuts across Cloud, Data, Dynamics, Contact Centers, and around newer technologies like Ge

Job Title:

Data Science Engineer

Experience:

4-8 years

Role Summary:

Role Overview:

The

Microsoft Fabric Developer

will be responsible for designing, developing, and maintaining

end-to-end data and analytics solutions

using the

Microsoft Fabric platform

. The role involves working across

Data Engineering

,

Data Science

, and

Business Intelligence

components within Fabric -- leveraging

Data Factory

,

Lakehouse

,

Data Engineering

,

Data Science

, and

Power BI

experiences to deliver scalable, governed, and business-ready insights.

This position requires strong technical expertise in

Microsoft Fabric architecture

,

Power BI

, and

Azure data services

, coupled with the ability to translate business needs into performant, automated data pipelines and analytical models.

Key Responsibilities:

Data Ingestion & Integration

+ Design and implement

data ingestion pipelines

using

Microsoft Fabric Data Factory

.

2. Data Engineering & Modeling

+ Build

Lakehouses, Warehouses

, and

Data Models

using Fabric Data Engineering capabilities.

3. Business Intelligence & Visualization

+ Develop

semantic models

and

interactive dashboards

using

Power BI within Fabric

.

4. Collaboration & Automation

+ Collaborate with

Data Scientists

,

Analysts

, and

Business SMEs

to support ML model training and deployment pipelines within Fabric.

5. Governance & Best Practices

+ Implement

data security, RBAC, sensitivity labels

, and

data sharing policies

in Fabric

Required Skills & Experience:

+ 4-8 years of experience in

data engineering, BI, or analytics

, with at least 1 year in

Microsoft Fabric

.
+ Strong proficiency in

Microsoft Fabric components

, including:

- Data Factory, Lakehouse, Data Engineering, Data Science, Warehouse, Power BI, OneLake.+ Advanced skills in

SQL

,

PySpark

, and

Data Modeling

.
+ Experience with

Power BI datasets, DAX, and data visualization best practices

.
+ Familiarity with

Microsoft Purview

for governance and

Entra ID (Azure AD)

for access control.
+ Understanding of

ETL/ELT pipelines

,

CI/CD for data pipelines

, and

Azure DevOps

integration.
+ Exposure to

Azure Synapse

,

Databricks

, or

Azure Data Lake

migration to Fabric.

Good-to-Have Skills:

+ Experience integrating

Microsoft Fabric with Copilot and GenAI-based insights

.
+ Knowledge of

Python, Notebooks

, or

ML model deployment

within Fabric Data Science experience.
+ Understanding of

RAG pipelines

,

AI-driven analytics

, or

Semantic Kernel

integration.
+ Certification:

Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)

.
+ Exposure to

D365 data sources

,

Power Platform

, or

Azure Data Factory (legacy)

.

Education:

+ Bachelor's or master's degree in computer science, Data Engineering, Information Systems, or a related field.

Soft Skills:

+ Strong analytical and problem-solving skills.
+ Excellent collaboration and communication abilities.
+ Ability to translate business needs into data-driven outcomes.
+ Focus on performance optimization, governance, and automation.