Data Engineer

3 weeks ago


Trivandrum, India Litmus7 Full time
About the OrganizationLitmus7 Systems Consulting Pvt. Ltd. is a Retail Maximization company specialized in accelerating digital revenue and profitability for Retailers, Brands and CPGs. The full spectrum of Litmus7’s Retail Maximization services include solutions, products and concepts that are essential for a retailer’s survival in this fast changing consumer industry, coupled with technology services to stabilize and scale their digital ecosystem.Rated No.1 in credibility, we're a partner to the top 5 global retailers in Grocery, Fashion, Beauty, Pet Care and General Merchandise. A network of five worldwide centers across USA, India, Canada, UK and UAE are driven by 400 plus specialist technologists, who are passionate creators and problem-solvers.We are a visionary organization conceptualizing the future of retail that the world can build on. Our retail innovation ecosystem upheld by the retail maximization team is headed by a bunch of creative technologists dedicated to building products that will empower the digital journey of consumers. We believe the future of retail is consumer driven and is aspiring to democratize the digital world.Envisioning to power the next era of Retail, we work on cutting edge technologies. Our AI Team is the center of excellence for incubating and nurturing talent with deep functional expertise in Artificial Intelligence and Machine Learning.

Job Description

Design, develop, and maintain scalable and efficient big data processing pipelines distributed computing systemsCollaborate with cross-functional teams to understand data requirements and design appropriate data solutions.Implement data ingestion, processing, and transformation processes to support various analytical and machine learning use cases.Optimize and tune data pipelines for performance, scalability, and reliability.Monitor and troubleshoot pipeline performance issues, identifying and resolving bottlenecks.Ensure data quality and integrity throughout the pipeline, implementing data validation and error handling mechanisms.Stay updated on emerging technologies and best practices in big data processing and analytics, incorporating them into our data engineering practices.Document design decisions, technical specifications, and data workflows.


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