Description:

As a Principal Data Engineer (Azure) at Tiger Analytics, you will work with Azure cloud, Databricks, and Data Modelling to build various analytics solutions & platforms, data lakes, modern data platforms, and data fabric solutions on Microsoft Azure.
You will design and build scalable data ingestion pipelines for batch and streaming datasets, execute high-performance data processing for structured and unstructured data, and harmonize data.
Your responsibilities will include scheduling, orchestrating, and validating pipelines, designing exception handling and log monitoring, making tech stack decisions, and collaborating with multiple teams and stakeholders to bring Analytical Solutions to life.

Requirements:

Hands-on experience with Azure Data Factory (ADF), PySpark, Databricks, ADLS, and Azure SQL Database is mandatory.
Optional knowledge of Azure Synapse Analytics, Event Hub & Streaming Analytics, Cosmos DB, and Purview.
Strong programming, unit testing, and debugging skills in SQL, Python, or Scala/Java are required.
Experience with big data technologies like Hadoop, Spark, Airflow, NiFi, Kafka, Hive, Neo4J, and Elastic Search.
Understanding of file formats such as Delta Lake, Avro, Parquet, JSON, and CSV.
Familiarity with Agile projects, DevOps processes, Git, Jenkins, and Azure DevOps.
Good to have experience with Data Lake & Lakehouse projects, building REST services, and supporting BI and Data Science teams.
Certifications like Data Engineering on Microsoft Azure (DP-203) or Databricks Certified Developer (DE) are a valuable addition.

This position provides an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.