Data Engineer (Azure/Manager)

Roles & responsibilities

•As an Advisory Lead in this team, you will play a key role in strategizing, designing, and delivering Azure data engineering and analytics solutions for clients

•Ability to drive discussions with clients to understand their data engineering, analytics, and platform modernization requirements and provide domain‑led advisory support

•Lead and manage engagements involving data platform modernization, data migration, data integration, and analytics transformation on Azure

•Design and implement scalable, secure, and high‑performance cloud-based data architectures leveraging Azure native services

Roles & responsibilities

•Ability to identify and recommend the most suitable Azure data engineering patterns, tools, and services based on client use cases and environments

•Work closely with cross‑functional teams including cloud architects, analytics teams, data scientists, and business stakeholders

•Drive adoption of industry best practices in data modeling, data quality, security, governance and performance optimization

•Continue to cultivate a culture of collaboration, innovation, and engineering excellence

•Maintain strong technical and industry knowledge of trends in big data, analytics, cloud-native data platforms, and agile delivery models

•Ensure cost-effective data platform design and usage through FinOps, performance tuning, and capacity planning on Azure

•Involve with Cloud & Data Engineering team in leadership forums, capability building initiatives, and pre-sales activities

Educational qualifications

•A bachelor's or master's degree in Engineering, Computer Science, or equivalentor equivalent

•Relevant Azure Certifications (Azure Solutions Architect Expert (AZ-305), Fabric Data Engineer Certificate (DP-700)

Work experience

•Proven experience in designing and delivering enterprise-scale Azure data engineering solutions

•8+ years of programming experience along with development experience.

•Hands-on experience in data migration and modernization initiatives, including on‑premises to Azure transitions

Mandatory technical & functional skills

•Strong experience in designing and implementing Azure data platforms using services such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure SQL, Azure Databricks, Fabric

•Deep understanding of data modeling concepts, dimensional modeling, and analytical data design patterns

•Experience with data lakes, data warehouses, real‑time and batch data processing pipelines

•Strong hands-on experience with SQL, PySpark, Python, and performance optimization techniques

•Experience building and maintaining ETL/ELT pipelines for structured and semi‑structured data

•Knowledge of streaming and near real-time data processing using Event Hubs, Kafka, or equivalent

•Experience with REST APIs and data integrations with enterprise and third‑party systems

•Strong understanding of data security, identity and access management, encryption, and compliance in Azure

•Experience implementing CI/CD pipelines for data engineering workloads using Azure DevOps or equivalent tools

•Familiarity with Agile delivery models and secure data engineering best practices

•Experience leading or mentoring a team of data engineers and providing technical guidance

•Excellent verbal and written communication skills with the ability to collaborate effectively across technical and business teams

•Support pre-sales activities, including solutioning, client presentations, demos, and technical inputs for proposals and RFPs

Preferred technical & functional skills

•Experience with serverless and cloud-native data processing using Azure Functions and Logic Apps

•Knowledge of data governance and cataloging tools such as Microsoft Purview

•Experience supporting advanced analytics, BI, and reporting workloads (Power BI, Synapse SQL, etc.)

•Understanding of AI/ML data enablement for analytics and data science use cases

•Exposure to Generative AI concepts, data preparation for LLMs, and integration with Azure OpenAI services