Azure Data Engineer

Artech L.L.C.; Dadri; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Artech L.L.C. is seeking an experienced Data Engineer to design, develop, and maintain enterprise-scale Data Warehouse solutions. You will build robust data pipelines, optimize data models, and manage large-scale data platforms to support analytics and decision-making.

The role emphasizes data governance, scalable ETL/ELT processes, and collaboration with analytics, AI initiatives, and business stakeholders to deliver trusted data assets across the organization.

Qualifications

• Strong expertise in SQL and relational databases.

Responsibilities

• Design, develop, and maintain enterprise Data Warehouse solutions.

Skills

SQL

Relational databases

Data Warehouse

ETL/ELT

Fact & Dimension Modeling

Data Lakes

PySpark

Python

Git

Azure DevOps

CI/CD

Tools

Databricks

Job description

We are seeking an experienced Data Engineer to design, develop, and maintain enterprise-scale Data Warehouse solutions. The ideal candidate will be responsible for building robust data pipelines, optimizing data models, managing large-scale data platforms, and ensuring high-quality, trusted data assets that support analytics, AI, and business decision-making.

The candidate will be responsible for designing, developing, and maintaining scalable data pipelines, data warehouses, and data lakes. The role will involve working with cloud-based data platforms and collaborating with technical and business teams to deliver reliable, high-quality data solutions. Experience in AI-enabled data solutions is highly desirable.

Key Responsibilities

Data Warehouse Development

• Design, develop, and maintain enterprise Data Warehouse solutions.
• Build and manage dimensional data models including Fact and Dimension tables.
• Define and maintain enterprise data architecture standards.
• Design and build ETL/ELT pipelines for structured and unstructured data sources.
• Develop scalable data ingestion, transformation, and integration frameworks.
• Ensure data quality, integrity, reconciliation, and validation.
• Implement automated data processing and orchestration workflows.
• Support batch and near real-time data processing requirements.

SQL & Data Optimization

• Develop and optimize complex SQL queries, stored procedures, functions, and views.
• Perform database tuning, query optimization, and performance monitoring.
• Ensure efficient storage utilization and processing performance across data platforms.
• Develop and support cloud-based data ecosystems.
• Build and maintain solutions using:
  • Databricks
• Support migration and modernization of legacy data platforms.

Data Governance & Security

• Implement data governance, metadata management, lineage, and data quality standards.
• Ensure compliance with organizational security policies and regulatory requirements.
• Support audit readiness and data protection initiatives.
• Work closely with business stakeholders, architects, application teams, and data consumers.
• Participate in solution design, code reviews, testing, deployment, and production support.
• Create and maintain technical documentation and architectural artifacts.

Required Technical Skills

Mandatory Skills

• Strong expertise in SQL and relational database technologies.
• Hands-on experience in enterprise Data Warehouse architecture and implementation.
• Experience designing and implementing ETL/ELT solutions.
• Strong understanding of:
  • Fact and Dimension Modeling
  • Data Lakes and Modern Data Platforms

Programming Languages : Python, SQL, PySpark

Good to have skills: Version Control & DevOps- Git, Azure DevOps, CI/CD Practices

Desirable AI & Advanced Data Capabilities

Experience in any of the following areas will be considered an added advantage:

• Building data platforms that support Generative AI and Machine Learning workloads.
• Experience with AI-enabled data processing, intelligent document extraction, and semantic search solutions.
• Exposure to Large Language Models (LLMs) such as Azure OpenAI, OpenAI, Claude, Gemini, or similar platforms.
• Data preparation and optimization techniques for AI and Machine Learning applications.
• Knowledge of Vector Databases, Embeddings, Retrieval-Augmented Generation (RAG), and AI knowledge repositories.
• Experience integrating AI services into enterprise applications and data platforms.
• Familiarity with copilots, AI agents, and workflow automation solutions.

Education