BigData -Spark, BigData, BI/BA

Key Skills

Apache Cassandra, Apache Kafka, API, AWS, Azure, Big Data Technology, Cloud computing, Databricks, ETL frameworks, Google Cloud Platform (GCP), HBase, MongoDB, NoSQL, PySpark, Python Programming, RabbitMQ, Scala Programming, Spark Core, SQL, SQL Server, T-SQL, XML-JSON

Job Description

Mandatory Skills:

• Azure SQL Server/TSQL
• Azure Integrated run-time
• Azure data factory
• Azure data bricks
• Azure data (delta) lakes
• Apache Spark/Scala/SQL

Responsibilities:

• Design & Implement Data ingestion and Data lakes-based solutions 

using Big Data Technologies.

• The Tech Lead should be highly proficient in the use of Big Data / Open- Source Technologies and standard techniques of Data Integration, 

Data Manipulation.

• Should be able to design and develop cost efficient and performant data pipelines in the cloud platform
• Create data environment to support our data analytics, reporting and data science teams
• Experience with integration of data from multiple data sources
• Knowledge of various Data Pipeline techniques and frameworks
• Performance optimization - need to monitor the complete process and apply necessary infrastructure changes to speed up the query execution.
• Efficient data ingestion - Discovering patterns in data sets with data mining techniques and using different data ingestion APIs and inject data into the data lake as per need.

The Role offers:

• Great opportunities to learn various tools and technologies used in a sophisticated data architecture within the Business Intelligence and Analytics Data Services
• Gives an opportunity to showcase candidates’ strong analytical skills and problem-solving ability
• An outstanding opportunity to re-imagine, redesign, and apply technology to add value to the business and operations
• Grow into a Technical architect role over a period

Essential Skills:

• 6+ Years hands on knowledge on SQL as well as SQL/NoSQL databases
• Proficient in programming languages such as Python, PySpark, Scala and Java
• Experience with Spark
• Working knowledge of XML, ETL, API and Web Services
• Experience with integration of data from multiple data sources
• Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
• Knowledge of various ETL techniques and frameworks, such as Flume
• Experience with various messaging systems, such as Kafka or RabbitMQ
• Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
• Working knowledge and experience in Big data services in one of the Cloud Provider will be good (AWS or Azure or GCP) 

Essential Qualification:

• BE/Btech in Computer Science, Engineering or relevant field.