Nomiso - Data Engineer - Big Data Technologies

Roles and Responsibilities :

• Create and maintain efficient and scalable data models as per business needs
• Create and maintain optimal data pipelines against multiple data sources lie SQL, BigData on Azure / AWS cloud;
• Assemble and process large, complex data sets to meet both functional and non-functional business requirements;
• Analyze and improve existing data models, pipelines, related infrastructure and processes
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics;
• Monitor and improve data quality and data governance policies
• Collaborate with stakeholders including the executive, product, data and design teams to assist with data-related technical issues and support their data infrastructure needs;
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader;
• Work with data and analytics experts to strive for greater functionality in our data Have Skills :
• 5+ years of experience working with distributed data technologies (e. Hadoop, MapReduce, Spark, Kafka, Flink etc) for building efficient, large-scale 'big data' pipelines;
• Strong Software Engineering experience with proficiency in at least one of the following programming languages : Java, Scala, Python or equivalent;
• Implement data ingestion pipelines both real time and batch using best practices;
• Experience with building stream-processing applications using Apache Flink, Kafka Streams or others;
• Experience with Cloud Computing platforms like Azure,Amazon AWS, Google Cloud etc.;
• Experience supporting and working with cross-functional teams in a dynamic environment;
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with ELK stack.
• Ability to work in a Linux to Have :
• Experience in building distributed, high-volume data services;
• Experience with big data processing and analytics stack in AWS : EMR, S3, EC2, Athena, Kinesis, Lambda, Quicksight etc.;
• Knowledge of data science tools and their integration with data lakes;
• Experience in container technologies like :
• Bachelor of Science in Computer Science or equivalent technical training and professional

(ref : hirist.tech)