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:
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.
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