Job Title

Job Overview:We are seeking a highly skilled Senior Data Engineer with deep expertise in Microsoft Azure data ecosystem to design, develop, and maintain scalable data pipelines and architectures. The ideal candidate will play a key role in building robust data solutions that support advanced analytics, BI, and AI workloads across the organization. This role involves working with cross-functional teams — data scientists, analysts, and business stakeholders — to ensure high-quality, secure, and performant data delivery.Total experience : 8 to 10 yearsKey Responsibilities:1. Data Architecture & Pipeline Development- Design, develop, and maintain data ingestion, transformation, and storage pipelines using Azure Data Factory, Azure Databricks, and Synapse Analytics. - Build end-to-end ETL/ELT workflows from diverse sources such as APIs, on-prem databases, SaaS applications, and data lakes. - Implement data modeling (star schema, snowflake, data vault, etc.) for analytical and operational data stores. - Manage data ingestion frameworks for both batch and streaming (real-time) use cases using Azure Event Hubs / Azure Stream Analytics / Kafka.2. Data Management & Governance- Ensure data quality, consistency, and integrity across all environments. - Implement and enforce data governance standards, including metadata management, lineage tracking, and data cataloging (e.g., Azure Purview). - Manage security, compliance, and access controls using Azure Active Directory (AAD) and RBAC principles. - Automate data validation, auditing, and monitoring workflows using modern DevOps practices.3. Cloud & DevOps Integration- Manage and optimize Azure Data Lake Storage (ADLS Gen2) for cost and performance. - Leverage Infrastructure as Code (IaC) tools such as Terraform, Bicep, or ARM templates for environment provisioning. - Implement CI/CD pipelines for data workflows using Azure DevOps / GitHub Actions. - Optimize compute and storage costs while maintaining scalability and resilience.4. Collaboration & Leadership- Partner with data scientists, BI developers, and product teams to deliver reliable data solutions. - Mentor junior data engineers on best practices, coding standards, and Azure services. - Participate in architectural reviews and contribute to data platform design decisions. - Communicate technical insights and trade-offs to non-technical stakeholders effectively.-Core Azure Services:- Azure Data Factory (ADF) – pipeline orchestration, triggers, linked services, integration runtime. - Azure Databricks – PySpark, Delta Lake, notebooks, job orchestration. - Azure Synapse Analytics – dedicated and serverless SQL pools, data modeling, query optimization. - Azure Data Lake Storage (ADLS Gen2) – hierarchical namespace, lifecycle management. - Azure Functions / Logic Apps – event-driven data workflows. - Azure Event Hubs / Kafka / Stream Analytics – real-time data ingestion.Programming & Tools:- Strong in Python or Scala for data transformations. - Proficient in SQL (T-SQL, Spark SQL, or Synapse SQL). - Experience with PySpark for distributed data processing. - Knowledge of Git, CI/CD, and DevOps best practices. - Familiarity with Power BI integration or other reporting tools is a plus.Data Architecture & Modeling:- Expertise in data warehouse design, data lakehouse architecture, and data pipelines. - Understanding of data partitioning, indexing, and query optimization techniques. - Experience with dimensional modeling, slowly changing dimensions, and fact tables.Other Skills:- Experience with API-based data ingestion and RESTful integrations. - Exposure to machine learning data pipelines or feature stores is a plus. - Familiarity with cost optimization and performance tuning in Azure.Soft Skills- Excellent analytical and problem-solving abilities. - Strong communication and documentation skills. - Ability to work in an agile, fast-paced environment. - Proven experience collaborating in cross-functional teams. - Self-driven with a passion for data engineering and cloud technologies.