[Hiring] Azure Data Engineer @Spruce Infotech

Role Description

We are seeking a Data Engineer with 3-5 years of experience to design, build, and support scalable data pipelines and cloud-based analytics solutions. The role requires hands-on expertise in ETL/ELT, Snowflake, Azure Data Factory, and Azure Databricks, with a strong focus on data quality, performance, reliability, and secure delivery.

Responsibilities

• Design, develop, test, deploy, and maintain batch and near-real-time ETL/ELT pipelines for structured and semi-structured data.
• Build and orchestrate ingestion and transformation workflows using Azure Data Factory and Azure Databricks.
• Develop scalable data models, transformations, stored procedures, and performance-optimized workloads in Snowflake.
• Use PySpark, Python, and SQL to cleanse, integrate, validate, and transform data across cloud and enterprise sources.
• Implement monitoring, logging, alerting, retry, and error-handling mechanisms to improve pipeline reliability.
• Apply data-quality checks, reconciliation controls, lineage, documentation, security, and access-control standards.
• Collaborate with architects, analysts, application teams, and business stakeholders to translate requirements into data solutions.
• Participate in code reviews, CI/CD deployments, production support, root-cause analysis, and continuous optimization.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 3-5 years of hands-on experience in data engineering, data integration, or cloud data-platform development.
• Strong experience designing ETL/ELT pipelines and working with dimensional/data-warehouse concepts.
• Hands-on proficiency with Snowflake, including data loading, transformations, query tuning, and warehouse optimization.
• Practical experience with Azure Data Factory for linked services, datasets, pipelines, triggers, and orchestration.
• Practical experience with Azure Databricks, Apache Spark/PySpark, notebooks, clusters, and Delta Lake concepts.
• Strong SQL skills and working proficiency in Python; experience integrating relational, file, API, and cloud-storage sources.
• Understanding of Git-based version control, CI/CD, Agile delivery, and secure cloud data practices.
• Strong analytical, troubleshooting, communication, and documentation skills.

Preferred Skills

• Azure Data Lake Storage Gen2
• Delta Lake
• Azure DevOps
• Git
• REST APIs
• Data governance/lineage
• Snowpipe
• dbt
• Microsoft Azure or Snowflake certifications