Cloud Data Architect

1 day ago

Pune, Maharashtra, India beBeeDataEngineer Full time ₹ 20,00,000 - ₹ 25,00,000
Senior Data Engineer

We are seeking a highly skilled Senior Data Engineer to fill this key role. The ideal candidate will have a strong background in designing and maintaining cloud-based data architectures, including data lakes, lakehouses, and warehouses.

The successful candidate will be responsible for building scalable real-time and batch processing workflows using Azure Databricks, PySpark, and Apache Spark. They will also perform data pre-processing, including cleaning, transformation, deduplication, normalization, encoding, and scaling to ensure high-quality input for downstream analytics.

In addition, the Senior Data Engineer will design and maintain cloud-based data architectures, deploy and optimize data solutions on cloud platforms with a focus on performance, security, and scalability. They will also develop and optimize Extract, Transform, Load/Extract, Load (ETL/ELT) pipelines for structured and unstructured data from various sources.

The ideal candidate will have experience working with containerization tools like Docker and Kubernetes for scalable data processing, as well as collaborating with automation teams, data scientists, and engineers to provide clean, structured data for artificial intelligence/machine learning models.

Key Responsibilities:

  • Build scalable real-time and batch processing workflows using Azure Databricks, PySpark, and Apache Spark.
  • Perform data pre-processing, including cleaning, transformation, deduplication, normalization, encoding, and scaling.
  • Design and maintain cloud-based data architectures, including data lakes, lakehouses, and warehouses.
  • Deploy and optimize data solutions on cloud platforms.
  • Develop and optimize ETL/ELT pipelines for structured and unstructured data.
  • Automate data workflows using Continuous Integration/Continuous Deployment (CI/CD) and DevOps best practices.

Requirements:

  • 4+ years of experience in data engineering.
  • Strong knowledge of Azure Databricks, PySpark, and Apache Spark.
  • Experience working with cloud-based data architectures, including data lakes, lakehouses, and warehouses.
  • Ability to design and maintain complex data pipelines.
  • Collaborative mindset and excellent communication skills.

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