Data Architect (Microsoft Fabrics)

Job Description:

Experience: 10+ Years

Job Summary

We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.

Key Responsibilities

• Design end-to-end data architecture using Microsoft Fabric.
• Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
• Define data ingestion, ETL/ELT, governance, security, and performance strategies.
• Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
• Work with business stakeholders to translate requirements into technical solutions.
• Mentor engineering teams and provide technical leadership.

Required Skills

• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
• Azure Data Engineering
• Power BI
• Azure AI Services / Azure OpenAI
• Data Architecture & Data Modeling
• SQL, Python
• Azure DevOps, CI/CD
• Strong stakeholder management and solution design experience
• 
  

Preferred: Experience in Capital Markets or Financial Services and Microsoft Azure/Fabric certifications.

NOTE: One technical round is mandatory to be taken F2F from office.

Data Engineer – Microsoft Fabric

Location: Pune, India

Work Mode: Hybrid

Experience: 6+ Years

Employment Type: Full-time contactor

Compensation: As per market standards, commensurate with experience and expertise

Shift Timings: 2:00 PM – 11:00 PM IST

Notice Period: 0 – 15 days

About the Role

Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.

We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.

The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.

Roles and Responsibilities

• Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
• Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
• Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
• Implement Medallion Architecture using Bronze, Silver and Gold layers.
• Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
• Develop and maintain data models, tables, views and optimized SQL queries.
• Build and support semantic models for Power BI and analytical workloads.
• Implement data quality, validation, monitoring and error-handling mechanisms.
• Work with metadata, lineage and governance requirements using Microsoft Purview.
• Implement data security, access controls and role-based permissions across data platforms.
• Support Data Product and domain-oriented data architecture principles.
• Follow DataOps practices including CI/CD, deployment, monitoring and production support.
• Troubleshoot pipeline failures, performance issues and data quality problems.
• Optimize data pipelines, queries and storage for performance and cost efficiency.
• Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
• Participate in technical design discussions, code reviews and architecture reviews.
• Maintain technical documentation, data flow diagrams and pipeline documentation.
• Support production deployments, incident resolution and SLA-driven data platform operations.
• Identify opportunities for automation and AI-assisted improvements across data engineering processes.

Qualifications and Skills

• 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
• Strong hands-on experience with Microsoft Fabric.
• Experience with:
• Microsoft Fabric Lakehouse
• Fabric Warehouse
• OneLake
• Fabric Data Factory / Pipelines
• Semantic Models
• Strong understanding of Lakehouse and Medallion Architecture.
• Strong SQL development and query optimization skills.
• Hands-on experience with Python and/or PySpark.
• Experience developing enterprise ETL/ELT and data integration pipelines.
• Experience with batch and incremental data processing.
• Understanding of data modelling concepts including dimensional modelling.
• Knowledge of data quality, metadata, lineage and data governance.
• Working knowledge of Microsoft Purview.
• Understanding of Data Mesh and Data Product concepts.
• Experience with CI/CD, version control, monitoring and DataOps practices.
• Understanding of cloud security, access controls and data privacy.
• Good troubleshooting and problem-solving skills.
• Strong communication skills and ability to work with distributed and client-facing teams.

Preferred Skills

• Microsoft Fabric or Azure Data certifications.
• Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
• Experience implementing Medallion Architecture on Microsoft Fabric.
• Experience with Power BI and semantic modelling.
• Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
• Experience working with Data Products or domain-oriented data solutions.
• Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
• Experience working with US or international enterprise clients.

What We Expect

The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.

10+ years of experience in Data Architecture, Data Engineering, or Data Platforms

• Strong expertise in IBM DB2 / On-Prem Relational Databases

• Strong expertise in PostgreSQL

• Hands-on experience with the Azure Data Ecosystem, including:

▪ Azure Data Factory (ADF)

▪ Azure Data Lake Storage Gen2 (ADLS Gen2)

▪ Azure Databricks / Synapse Analytics

▪ Azure Event Hub / Service Bus

▪ Azure Functions

Solution Architect – AZURE Data Engineering

Job Overview

We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.

Key Responsibilities

• Design and implement scalable data architecture and solutions.
• Develop and manage Data Warehouse and Data Lake architectures.
• Design data platforms using Medallion Architecture.
• Lead Data Engineering and ETL activities.
• Work with Azure Synapse Analytics for data processing and analytics.
• Develop data solutions using PySpark / Apache Spark.
• Define and implement data validation and data quality processes.
• Collaborate with business, data, and technology teams to deliver effective data solutions.

Required Skills

• Strong experience in Solution Architecture / Data Architecture.
• Strong knowledge of Data Warehouse and Data Lake architecture.
• Good understanding of Medallion Architecture.
• Strong experience in Data Engineering and ETL.
• Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
• Strong knowledge of PySpark / Apache Spark.
• Experience with Data Validation and Data Quality.
• Good communication and stakeholder management skills.
• 
  

Experience

8+ Years

Job Description

• Design and Implement Data Solutions: Lead the design, development, and implementation of scalable and secure Azure-

based data platforms, ensuring integration with various data sources and business systems. Deliver at least 2 major

projects every year with a focus on data engineering best practices.

• Optimize Data Pipelines: Build and optimize end-to-end data pipelines using Azure Data Factory, Azure Databricks, and

Azure Synapse, with an emphasis on automating data workflows. Achieve a 20% reduction in pipeline execution times

within the first 6 months.

• Cloud Infrastructure Management: Manage and maintain the Azure data environment, ensuring high availability, disaster

recovery, and cost optimization. Track and improve system uptime to exceed 99.9% reliability.

• Collaborate with Cross-Functional Teams: Partner with data scientists, data analysts, and business stakeholders to translate

business requirements into efficient data solutions. Facilitate at least 3 collaborative sessions per quarter to address key

business use cases.

• Ensure Data Security & Compliance: Implement data security measures, ensuring compliance with industry regulations

(GDPR, HIPAA, etc.) and company policies. Achieve and maintain full compliance in all data environments within the first

quarter of onboarding.

• Continuous Learning & Knowledge Sharing: Stay up-to-date with emerging Azure technologies, and mentor junior

engineers to promote knowledge sharing. Complete 1 Azure certification annually and conduct at least 2 internal

knowledge-sharing sessions per year.

• Sound knowledge of data governance practices, data quality management, and data security principles.

• Play a pivotal role in shaping our organization's data-driven journey, driving innovation through data analytics and insights.

• Optimize data storage, processing and retrieval mechanisms for performance, cost, and scalability using data storage

services (such as Azure Data Lake Storage, Azure SQL Database, etc.), data processing services (such as Azure Data Bricks,

Azure Synapse, etc.) and data visualization (PowerBI, Qlik, etc.) & integration services (Data API builder, logic apps, etc.)

• Monitor and troubleshoot data platform performance, identify and resolve issues, and provide recommendations for

continuous improvement.

• Collaborate with DevOps teams to automate deployment, configuration, and monitoring processes using Azure DevOps,

PowerShell, or other relevant tools.

• Stay up to date with the latest trends and advancements in cloud data services and provide recommendations on adopting

new technologies or features to enhance the data platform.

• Document technical designs, procedures, and guidelines for data platform engineering and operations

Knowledge, Skills & Experience

Job Experience • Bachelor's degree in Computer Science, Engineering, or a related field. Advanced

degree preferred.

• Proven 6-10 years experience in playing platform engineer or admin role

• Experience with big data technologies such as Apache Spark, Hadoop, or similar

frameworks.

• Solid understanding of cloud computing concepts and experience with cloud

infrastructure management and provisioning.

• Solid understanding of network security concepts and technologies (such as

firewalls, VPNs, intrusion detection/prevention systems, etc.) and data security

concepts and technologies (such as access controls, encryption, observability,

privacy laws/regulations, etc.)

• Experience in a Retail setup is preferred.

Required Skills The position will require someone with the following:

• Strategic Planning

Public

• Communication and Collaboration

• Problem Solving Skills A/B testing & experimentation

• SQL, BI tools, and storytelling with data

Dear Candidate,

Greeting from NAM Info Pvt Ltd.

We have a role for Data Engineer position with NAM Info.

This role will be permanent with NAM info and deploy to client

location NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA.

Work Mode: WORK FROM OFFICE

A decent hike can be provided based on current CTC

Interview Mode: Virtual

Role Descriptions:

Exp Range: 7 - 10 years

City Locations: NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA

Key Responsibilities*

Role: Data Engineer

Location: ~NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA

Skills: Digital: Databricks, Azure Data Factory

Experience Required: 8-10

Descriptions:

Good information and sound knowledge in Azure Synapse Analytics Azure Data Factory (ADF)Big Data technologies and data processing frameworks Azure Data Warehouse and associated Azure data platform services Data integration| data modelling| and performance optimization

Desire candidate

• Candidate should have valid PF.

Regards,

NAM Info 

Azure Data Factory and Azure Databricks, processing 5 million+ records/week from 4+ source systems into a governed Lakehouse. 

Roles & Responsibilities

• Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration

of enterprise-wide data from diverse sources

• Build and optimize data engineering workflows using Databricks and PySpark

• Write efficient, high-performance SQL for data transformation and analysis

• Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing,

data models, and pipelines

• Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the

development lifecycle

• Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production

environments with proper change control processes

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions

• Ensure data quality, reliability, and performance across all pipelines and platforms

Ideal Candidate

1Strong Azure Databricks Engineer / Senior Data Engineer Profile

2Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

Example:

We are looking for an experienced Data Architect to design, develop, and manage the organization's enterprise data architecture. The candidate will be responsible for building scalable data platforms, ensuring data quality and governance, and supporting business analytics through modern data solutions.

Experience Required

Mention the minimum years of experience.

Example:

• Minimum 12 years of experience in Data Architecture, Data Engineering, or related fields.
• 5+ years of experience in the Banking/Financial Services domain is preferred.

Educational Qualification

Mention the required degree.

Example:

• BE/BTech in Computer Science, Information Technology, Software Engineering, Electronics & Communication Engineering, or equivalent.
• OR MCA/MTech/MSc in Computer Science, IT, or related disciplines.
• MBA is preferred.

Technical Skills

List the skills the candidate must have.

Example:

• AWS, Azure, or GCP
• Data Warehousing (DWH)
• ETL/ELT
• Database Management
• Data Modeling
• Data Analytics
• Data Lakes
• Data Governance

Key Responsibilities

Convert the points you received into simple action statements.

Example:

• Design and maintain enterprise data architecture.
• Develop data warehouses and data lakes.
• Define data standards and governance policies.
• Ensure data quality and security.
• Design ETL/ELT processes.
• Integrate data from multiple systems.
• Plan and execute data migration projects.
• Review existing data architecture and recommend improvements.
• Provide technical guidance to project teams.
• Evaluate new data technologies and tools.

Preferred Skills

These are not mandatory but are an advantage.

Example:

• Banking domain experience
• Strong analytical and problem-solving skills
• Good communication skills
• Leadership and stakeholder management
• Experience mentoring technical teams

Role Summary:

We are looking for an experienced Snowflake Lead to lead the design, development, migration, and optimization of enterprise data platforms using Snowflake. The candidate will provide technical leadership to data engineering teams and work closely with architects, business stakeholders, and application teams.

Key Responsibilities

• Lead the architecture and development of scalable Snowflake data warehouse solutions.
• Design and develop scalable Azure Data Factory (ADF) pipelines for API-based and batch data ingestion, implementing parameterized workflows, scheduling, and error handling.
• Build and optimize enterprise Snowflake data warehouse solutions using Snowflake SQL, Streams, Tasks, Stored Procedures, VARIANT data type, and LATERAL FLATTEN for semi-structured JSON processing.
• Integrate GraphQL and REST APIs using OAuth 2.0, implementing secure API authentication, JSON parsing, and API validation using Postman.
• Develop cloud-based data ingestion solutions using Azure Data Lake Storage Gen2 (ADLS) as the landing layer and Azure Key Vault for secure credential management.
• Design metadata-driven ELT frameworks with incremental loading, audit logging, watermark processing, and automated data orchestration.
• Optimize Snowflake performance through warehouse sizing, query tuning, clustering strategies, Time Travel, Cloning, and warehouse management best practices.
• Collaborate with DevOps teams using Azure DevOps for source control, CI/CD deployment, release management, and Agile delivery.
• Design dimensional data models, build curated data marts, and support enterprise reporting and analytics requirements.
• Develop and maintain Power BI semantic models, datasets, dashboards, and reports; knowledge of DAX, Power Query, and data visualization best practices is preferred.
• Work closely with business stakeholders, solution architects, and cross-functional teams to deliver secure, scalable, and high-performance cloud data platform solutions.

Thanks,

Mounika P