Data Engineer(Azure)

6 hours ago


Chennai, Tamil Nadu, India Photon Group Full time
Description

Greetings Everyone

Who are we? 


For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check 



What will you do?     What are we looking for? 

Position:  Data Engineer

 

Location: Chennai/Banglore/Hyderabad/Trivandrum, PST Timing

 

Job Summary

We are seeking a Data Engineer to work on a Generative AI initiative to join our team. The ideal candidate will have a deep understanding of data modeling, data schemas and has developed ETLs from various sources eensuring high data availability, fault tolerance and security and governance.

Responsibilities:

  • Collaborate with stakeholders to understand data requirements and design scalable and efficient data models, schemas, and architectures on the Azure platform.
  • Develop and implement data integration and ETL (Extract, Transform, Load) processes to ingest, transform, and load data from various sources into Azure data storage systems.
  • Build and maintain scalable and reliable data pipelines using Azure Data Factory, Azure Databricks, or similar tools to automate the movement and transformation of data.
  • Optimize data storage and retrieval mechanisms, ensuring high data availability, fault tolerance, and efficient query performance.
  • Hands-on experience with cloud platforms (MS Azure, AWS or Google Cloud Services)
  • Hands-on experience with distributed computing (preferably using Apache Spark or Databricks)
  • Monitor and troubleshoot data pipelines, identifying and resolving performance issues, data quality problems, and data integration challenges.
  • Collaborate with data scientists and analysts to provide them with access to reliable and well-structured data sets for analysis and reporting purposes.
  • Implement data governance and security measures to protect sensitive data, ensure compliance with regulatory standards, and adhere to data privacy policies.
  • Work closely with the DevOps team to automate deployment processes, ensure continuous integration and delivery of data solutions, and maintain infrastructure as code.
  • Stay updated with the latest advancements in Azure data services, evaluate and implement new tools and features to enhance data engineering processes. 

Requirements

  • Bachelor's or master's degree in computer science, Engineering, or a related field.
  • Proven experience as a Data Engineer, with a strong focus on Azure cloud platform.
  • In-depth knowledge of Azure data services such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure SQL Database, Azure Data Lake Storage, and Azure Cosmos DB.
  • Proficiency in designing and implementing scalable data models, data warehouses, and data lakes.
  • Strong understanding of ETL processes, data integration patterns, and data transformation techniques.
  • Experience with programming languages such as Python, SQL, and PowerShell for data manipulation, scripting, and automation.
  • Familiarity with big data technologies and frameworks like Hadoop, Spark, and NoSQL databases is a plus.
  • Strong analytical and problem-solving skills, with the ability to troubleshoot and optimize data pipelines.
  • Excellent communication and collaboration skills to work effectively in a team environment and interact with stakeholders from various disciplines.

Preferred Qualifications:

  • Bachelor's or master's degree in computer science, Data Science, Statistics, Math, Physics, or other Science related discipline with course work in AI/ML.
  • Cloud certifications preferred.
  • Contribute to the design and implementation of new data-driven solutions, using cutting-edge machine learning and artificial intelligence techniques.
  • Self-motivated with a strong desire to learn and stay up to date with new technologies in the field.
  • Ability to work collaboratively in a team environment and communicate complex technical concepts to non-technical stakeholders.


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