Job description 

At Thoucentric, we work on various problem statements.
 

• The most popular ones are -
  
  • Building capabilities that address a market need, basis our ongoing research efforts
     
  • Solving a specific use case for a current or potential client based on challenges on-ground
     
  • Developing new systems that help be a better employer and a better partner to clients
     
• All of these need the best of minds to work on them day-to-day; and we do exactly that! 
   
• Your contribution to organization development is as important as outward facing consulting. 
   
• We are invested in both, employee growth and client success!
   

Roles & Responsibilities
 

• Implement robust data pipeline using Microsoft Stack.
   
• Create reusable and scalable data pipelines.
   
• Development and deployment of new data platforms.
   
• Leverage Azure BI services for development of Big Data Platforms.
   
• Work closely with the Product Owners and Architects to develop Azure Data Platforms.
   
• Work with the leadership to set the standards for software engineering practices within the team and support across other disciplines.
   
• Produce high-quality code that allows us to put solutions into production.
   

Refactor code into reusable libraries, APIs, and tools.
 

Requirements

• Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
   
• 2-4 Years’ experience as a data engineer.
   
• 2+ Years’ experience using Azure Services like Data Lake, Data Factory, Databricks etc.
   
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
   
• Experience with relational SQL and NoSQL databases, including Postgres, MongoDB, Cassandra etc.
   
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
   
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
   
• Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.
   
• Understanding of infrastructure (including hosting, container-based deployments, and storage architectures) would be advantageous.
   
• Understanding of Lambda and Kappa architecture patterns preferred.