Azure Data engineer Walk In Drive at Noida

Tata Consultancy Services; Uttar Pradesh; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Tata Consultancy Services in Noida is hiring an Azure Data Engineer to design and implement scalable data pipelines and analytics solutions. You will ingest data from diverse sources, transform it with Spark on Azure, and store it in Azure Data Lake Storage and databases, collaborating with data scientists to enable insights.

Join a dynamic team to drive data-driven decisions using Azure data services and modern analytics tooling in a fast-paced environment.

Qualifications

• Strong proficiency in Python and PySpark for data ingestion and processing.
• Experience with ETL using Azure Data Factory.
• Hands-on with Azure Databricks and Azure Synapse Analytics.
• Knowledge of storage services: Azure SQL DB, Cosmos DB, Data Lake Storage, Blob Storage.
• Experience designing data models and warehousing with Azure Synapse.
• Collaborate with data scientists to build analytical models.

Skills

Python

PySpark

Data Ingestion

Data Transformation

Data Warehousing

Data Modeling

Education

Tools

Azure Data Factory

Azure Databricks

Azure Synapse Analytics

Azure SQL Database

Azure Cosmos DB

Azure Data Lake Storage

Azure Blob Storage

Azure Analysis Services

Azure DevOps

Azure Monitor

Azure Automation

Job description

TCS has been a great pioneer in feeding the fire of Young Techies like you. We are a global leader in the technology arena and there's nothing that can stop us from growing together.

TCS is Hiring for Azure Data Engineer

Experience Range: - 6+

Job Locations : Noida

Desired Competencies (Technical/Behavioral Competency)

Must-Have**

(Ideally should not be more than 3-5)

• Strong proficiency in Python, Pyspark. Data Ingestion and Integration: Ingest data from various sources such as databases, files, APIs, and streaming platforms into Azure. For example, you could use Azure Data Factory to orchestrate the extraction, transformation, and loading (ETL) of data from an on-premises SQL Server database to Azure Blob Storage.
• Data Transformation and Processing: Perform data transformation and processing tasks to prepare the data for analysis and reporting. Azure Databricks or Azure Synapse Analytics can be used for large-scale data transformations using tools like Apache Spark.
• Data Storage and Management: Select and manage the appropriate storage solutions for your data. For instance, you could use Azure SQL Database or Azure Cosmos DB for structured data, Azure Data Lake Storage for big data and unstructured data, or Azure Blob Storage for file storage.
• Data Warehousing: Implementing data warehousing solutions is a common use case for Azure Data Engineers. Azure Synapse Analytics (formerly Azure SQL Data Warehouse) offers scalable and distributed analytics capabilities for handling large datasets.
• Data Modeling and Analysis: Collaborate with data scientists and analysts to design and implement data models for analytical workloads. Azure Analysis Services or Azure Databricks can be used for building and deploying models to support interactive data analysis.

Good-to-Have

• DevOps and Automation: Automating data pipelines, monitoring data processes, and managing deployments are important tasks for Azure Data Engineers. They may use tools like Azure DevOps, Azure Monitor, and Azure Automation to achieve continuous integration and delivery.