Data Engineer( Snowflake & Azure)

Role Overview

We are seeking Data Engineers with 3 to 7 years of hands-on experience in developing, integrating, securing, and optimizing cloud data solutions, with a strong focus on Snowflake and Azure.

The ideal candidate should have strong expertise in Azure Synapse, Databricks, and Snowflake, along with proficiency in Python, SQL, PySpark, and cloud data engineering concepts. Exposure to Microsoft Fabric will be an added advantage.

The candidate will work closely with analytics, product, business, and engineering teams to build scalable, secure, reliable, and high-performance data solutions.

Required Skills & Qualifications

• 3to 7 years of professional experience in Data Engineering.
• B.Tech / B.E. in Computer Science, Information Technology, Engineering, or a related field.
• Strong hands-on experience with Azure Synapse Analytics, Databricks, and Snowflake.
• Proficiency in Python, SQL, PySpark, and Apache Spark.
• Strong understanding of ETL/ELT pipeline development, data ingestion, transformation, and processing.
• Experience designing and developing scalable data pipelines and data workflows for batch and near-real-time processing.
• Hands-on experience with Azure Data Factory and Azure Data Lake Storage (ADLS).
• Strong understanding of data warehousing, data modeling, dimensional modeling, and Lakehouse architecture.
• Experience working with Databricks, Delta Lake, Spark, and distributed data processing.
• Hands-on experience with Snowflake, including data warehousing, Snowpipe, Streams & Tasks, performance tuning, data sharing, and security/access management.
• Experience with Azure Synapse SQL pools and Spark-based data processing.
• Experience working with large-scale structured, semi-structured, and unstructured datasets.
• Strong understanding of data quality, validation, monitoring, troubleshooting, and performance optimization.
• Experience with version control, Git, CI/CD, testing, and deployment best practices.
• Knowledge of data security, governance, access control, and compliance practices.
• Exposure to Microsoft Fabric, including Fabric Data Factory, Fabric Lakehouse, Fabric Warehouse, and Fabric/Synapse integration.
• Familiarity with orchestration tools such as Azure Data Factory, Databricks Workflows, or Apache Airflow.
• Experience with streaming technologies such as Kafka, Azure Event Hubs, or Kinesis is an advantage.
• Familiarity with Power BI or other BI/analytics tools is an added advantage.
• Experience with CI/CD tools such as Azure DevOps, GitHub Actions, or Jenkins is preferred.
• Exposure to cloud data platform architecture, reusable data frameworks, and modern Lakehouse solutions is preferred.
• Basic understanding of ML/Data Science workflows is a plus.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Ability to work effectively in an Agile and fast-paced environment, with a strong ownership mindset and attention to detail.
• Azure, Databricks, Snowflake, or Microsoft Fabric certifications are an added advantage.