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Shape the Future with Dun & Bradstreet
At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We're a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what's next Join us! Explore opportunities at dnb.com/careers.
Designation: Senior Software Engineer - Big Data
Location: Hyderabad
About Us:
We are a global organization driven by a diverse community of professionals who bring unique experiences and perspectives to everything we do. Whether working from a corporate office or remotely, we stay connected by listening to our customers and collaborating on impactful solutions.
Our products and services power businesses of all sizes, across industries. At the core of our operations are our values: being data-inspired, relentlessly curious, and inherently generous. These values guide our decisions, shape our culture, and define how we work together.
Role Overview:
We are looking for a Senior Software Engineer - Big Data to design, build, and optimize modern data platforms and pipelines. This role requires strong expertise in big data technologies, cloud environments, and data engineering best practices, with a focus on scalability, performance, and innovation.
All Dun & Bradstreet job postings can be found at https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.
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Job ID: 149208541
Skills:
Performance Tuning, Azure Functions, Data Factory, Nosql, Cosmos DB, Python, Hadoop, Scala, Apache Spark, Sql, Hive, Databricks, Azure, Hbase, data marts, Big Data Frameworks, batch data processing, data quality validation, distributed databases, Eventhub, data lakes, Optimization, ETL pipeline development, Medallion architecture, Cloud platforms, Synapse, Datawarehouses, streaming pipelines
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