Job Description
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.
- Analyse 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 systems.
Must Have Skills :
- 5+ years of experience working with distributed data technologies (e.g. 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 environment.
Nice 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, Quick sight etc.;
- Knowledge of data science tools and their integration with data lakes;
- Experience in container technologies like Docker/Kubernetes.
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Posted By
Bharat Raj Medaboina
Head of Operations at INFOTECH CONSULTANCY PRIVATE LIMITED
Last Active: 30 Jul 2025
44
Posted in
Data Analytics & BI
Functional Area
Big Data / Data Warehousing / ETL
Job Code
1518021
