Lead Data Engineer / Data Architect

Siemens; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Siemens seeks a highly experienced Lead Data Engineer/Data Architect to own the design, implementation, governance, and delivery of enterprise data platforms across Digital Grid. You will combine architecture thinking with hands-on execution and lead multiple initiatives with autonomy.

The role requires deep expertise in data lakehouse patterns, Microsoft Fabric, and data product governance, with a focus on scalable, secure data foundations for analytics and AI workloads.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or equivalent practical experience.
• 9–12 years of experience in Data Engineering, Data Warehousing, BI, Analytics, and enterprise data platform delivery.
• Experience leading large-scale data initiatives from architecture to production deployment.

Responsibilities

• Own end-to-end delivery from requirements to architecture, implementation, deployment, documentation, and support.
• Design secure, scalable data lake/lakehouse/warehouse architectures with data products.
• Implement Fabric Lakehouse, Warehouse, OneLake, Data Factory, and Power BI integration patterns.
• Build metadata-driven ingestion/ transformation frameworks across ERP, CRM, Finance, HR, APIs, and external sources.
• Create dimensional models, data marts, semantic models, KPIs, and governed reporting layers for self-service BI.
• Define and enforce metadata, lineage, data quality, RBAC, RLS, retention, and compliance standards.
• Prepare curated datasets for AI/GenAI, RAG, forecasting, and analytics use cases.
• Lead design reviews, set engineering standards, mentor engineers, and drive documentation.
• Partner with stakeholders and leadership to translate business needs into scalable data solutions.
• Optimize data pipelines, queries, workloads, orchestration, monitoring, and production SLAs.

Skills

SQL

Python

PySpark

ETL/ELT

Data Modeling

Data Mesh

Power BI

RBAC

RLS

Azure Fabric

Education

Bachelor's/Master's in CS/IT/related

Tools

Azure Data Factory

Power BI

Git/GitHub

Azure Data Lake

Job description

About The Role

We are looking for a highly experienced Lead Data Engineer / Data Architect to own the design, implementation, governance, and delivery of enterprise data platforms supporting analytics, reporting, AI, and operational excellence initiatives across Digital Grid. This is not a developer-only role. The person should combine architecture thinking with hands-on implementation and provide technical leadership across multiple parallel initiatives.

This role is suited for a self-driven technical leader who can independently own workstreams, engage stakeholders, translate business requirements into scalable technical solutions, and drive delivery with a high degree of autonomy.

Key Responsibilities

• Solution Ownership & Delivery: Own end-to-end delivery from requirements to architecture, implementation, deployment, documentation, and support.
• Enterprise Data Architecture: Design secure, scalable data lake, lakehouse, warehouse, and data product architectures with reusable patterns.
• Microsoft Fabric Platform Engineering: Implement Fabric Lakehouse, Warehouse, OneLake, Data Factory, Semantic Models, and Power BI integration patterns.
• Metadata-Driven Engineering: Build reusable ingestion and transformation frameworks for ERP, CRM, Finance, HR, SharePoint, APIs, databases, files, and external sources.
• Data Modeling & Analytics Enablement: Create dimensional models, data marts, semantic models, KPIs, and governed reporting layers for self-service BI.
• Governance, Quality & Security: Define and implement standards for metadata, lineage, auditability, naming conventions, access control, retention, data quality, RBAC, RLS, and compliance.
• AI-ready Data Foundations: Prepare curated datasets, knowledge repositories, and governed data foundations for AI, GenAI, RAG, forecasting, and advanced analytics use cases.
• Platform Leadership & Reviews: Conduct design reviews, define engineering standards, mentor engineers, guide implementation teams, and drive reusable documentation.
• Stakeholder Management: Partner with business stakeholders, architects, and leadership to challenge assumptions, identify opportunities, and propose scalable approaches.
• Operational Reliability: Optimize datasets, queries, workloads, orchestration, monitoring, release processes, and production SLAs.

Education

• Bachelor's/Master's degree in Computer Science, Information Technology, Engineering, Data Science, or equivalent practical experience.

Experience

• 9-12 years of experience in Data Engineering, Data Warehousing, BI, Analytics, and enterprise data platform delivery.
• Minimum 3-5 years of experience designing cloud-based enterprise data platforms or modern lakehouse/warehouse architectures.
• Proven experience leading large-scale data initiatives from architecture and design through production deployment and support.
• Experience working with global stakeholders, Sr. Data/Solutions Architects, AI/ML Architects/Engineers, business users, and cross-functional engineering teams.

Core Technical Skills

• Data Engineering: Advanced SQL, Python/PySpark, ETL/ELT, API ingestion, incremental processing, monitoring, orchestration, and framework-based delivery.
• Data Architecture: Lakehouse, EDW, Medallion Architecture, dimensional modeling, star/snowflake schemas, data products, Data Mesh, and enterprise integration patterns.
• Microsoft Fabric & Azure: Fabric Lakehouse/Warehouse, OneLake, Data Factory, Power BI Semantic Models, Azure Data Lake, Azure SQL, ADF, Service Principals, RBAC, and workspace governance.
• BI & Semantic Modeling: Power BI, semantic models, tabular modeling, KPI frameworks, executive dashboards, and self-service analytics enablement.
• Governance & Security: Metadata management, lineage, quality, auditability, RBAC, RLS, privacy, compliance, retention, and governance frameworks.
• DataOps & DevOps: Git, GitLab/GitHub, Azure DevOps, CI/CD, automated testing, release management, monitoring, and observability.

Soft Skills

• Strong ownership mindset with ability to work independently and drive outcomes with minimal supervision.
• Excellent stakeholder management and communication skills across technical and non-technical audiences.
• Strong problem-solving, decision-making, prioritization, and ability to manage multiple workstreams.
• Ability to mentor engineers, guide implementation teams, and balance delivery speed with scalable design.

Preferred Qualifications

• Hands-on enterprise experience with Microsoft Fabric Lakehouse, Warehouse, OneLake, Data Factory, and Power BI semantic models.
• Experience implementing metadata-driven ingestion frameworks and medallion architecture in production.
• Experience modernizing legacy EDW, ETL, and reporting platforms to cloud-native data platforms.
• Experience integrating Microsoft 365, SharePoint Online, Microsoft Graph, Teams, and Entra ID with enterprise data platforms.
• Exposure to AI/ML and GenAI data requirements including RAG-ready repositories and enterprise search foundations.
• Experience in Energy, Utilities, Industrial IoT, Manufacturing, Engineering, Finance, or Enterprise Operations.
• Relevant certifications: Azure Data Engineer, Azure Solutions Architect, Microsoft Fabric Analytics Engineer, Snowflake, or Google Cloud certifications.