Senior Data Engineer

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 years

Key Responsibilities:

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.