
Responsibilities:
• Build customer facing solution for Data Observability product to monitor Data Pipelines
• Work on POCs to build new data pipeline monitoring capabilities.
• Building next-generation scalable, reliable, flexible, high-performance data pipeline capabilities for ingestion of data from multiple sources containing complex dataset.
•Continuously improve services you own, making them more performant, and utilising resources in the most optimised way.
• Collaborate closely with engineering, data science team and product team to propose an optimal solution for a given problem statement
• Working closely with DevOps team on performance monitoring and MLOps
Required Skills:
• 3+ Years of Data related technology experience.
• Good understanding of distributed computing principles
• Experience in Apache Spark
• Hands on programming with Python
• Knowledge of Hadoop v2, Map Reduce, HDFS
• Experience with building stream-processing systems, using technologies such as Apache Storm, Spark-Streaming or Flink
• Experience with messaging systems, such as Kafka or RabbitMQ
• Good understanding of Big Data querying tools, such as Hive
• Experience with integration of data from multiple data sources
• Good understanding of SQL queries, joins, stored procedures, relational schemas
• Experience with NoSQL databases, such as HBase, Cassandra/Scylla, MongoDB
• Knowledge of ETL techniques and frameworks
• Performance tuning of Spark Jobs
• General understanding of Data Quality is a plus point
• Experience on Databricks,snowflake and BigQuery or similar lake houses would be a big plus
• Nice to have some knowledge in DevOps

About Wissen Technology
About
The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015. Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains.
With offices in US, India, UK, Australia, Mexico, and Canada, we offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
Leveraging our multi-site operations in the USA and India and availability of world-class infrastructure, we offer a combination of on-site, off-site and offshore service models. Our technical competencies, proactive management approach, proven methodologies, committed support and the ability to quickly react to urgent needs make us a valued partner for any kind of Digital Enablement Services, Managed Services, or Business Services.
We believe that the technology and thought leadership that we command in the industry is the direct result of the kind of people we have been able to attract, to form this organization (you are one of them!).
Our workforce consists of 1000+ highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like MIT, Wharton, IITs, IIMs, and BITS and with rich work experience in some of the biggest companies in the world.
Wissen Technology has been certified as a Great Place to Work®. The technology and thought leadership that the company commands in the industry is the direct result of the kind of people Wissen has been able to attract. Wissen is committed to providing them the best possible opportunities and careers, which extends to providing the best possible experience and value to our clients.
Connect with the team
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Company: Miror – Women’s Hormonal Health Platform
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Location: On-Site (Bengaluru
Stipend: ₹20,000/ month
About Miror
At Miror, we’re on a mission to redefine how women experience midlife — especially during perimenopause, menopause, and beyond.
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Looking forward to connecting with Head of Sales – India is ready to shape a sustainable future with us!
Best Regards,
Indrani Dutta
Senior HR Manager
Miror Therapeutics Pvt. Ltd
Visit: www.miror.in
Visit: https://www.sohamenergy.in/
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