Weekday AI
BigDataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Big Data Engineer at Weekday AI. Skills: Big Data, Scala, Spark, Hadoop. Design scalable big data solutions. Develop scalable big data solutions”
What You'll Achieve.
deliver efficient and reliable data platforms; support business intelligence; support analytics; support data-driven decision-making
Industry & Context.
problem-solving ability; debugging skills; optimization skills
What They're Looking For.
Must Have
Scala, Apache Spark, Hadoop ecosystem, distributed data processing applications, data structures, algorithms, parallel processing concepts, large-scale ETL, data transformation pipelines, performance optimization, troubleshooting in big data environments, 4–8 years of experience in Big Data Engineering or Data Platform Development, handling structured and unstructured data at scale, Agile development environments
Nice to Have
Python, Hive, HDFS, Yarn, MapReduce, enterprise-level Big Data platforms, cloud-based data ecosystems, workflow orchestration and scheduling tools, real-time streaming technologies, DevOps practices, CI/CD pipelines for data engineering, high-volume data environments, enterprise data lakes, large-scale analytics platforms
What You'll Do.
Design scalable big data solutions
Develop scalable big data solutions
Maintain scalable big data solutions
Build data processing pipelines
Optimize data processing pipelines
Develop reusable frameworks
Develop reusable components
Work with distributed computing technologies
Implement high-performance Spark applications
Optimize data workflows
Collaborate with cross-functional teams
Monitor big data infrastructure
Troubleshoot big data infrastructure
Enhance big data infrastructure
Ensure data integrity
Ensure data consistency
Participate in architecture discussions
Participate in code reviews
Support deployment activities
Support automation activities
Support performance tuning activities
Stay updated with emerging technologies
Recommend improvements
How You'll Work.
Team & Collaboration
Collaborate closely with data architects; Collaborate closely with data scientists; Collaborate closely with software engineers; Collaborate closely with business stakeholders; Collaborate with cross-functional teams; contributing effectively within a collaborative team
Communication Scope
Excellent communication skills
Full Job Description
**This role is for one of the Weekday's clients** **Salary range: Rs 1500000 - Rs 2500000 (ie INR 15-25 LPA) ** Min Experience: 4+ years Location: Bengaluru JobType: full-time We are looking for a highly skilled and motivated Big Data Engineer with 4–8 years of experience in designing, developing, and optimizing large-scale data processing systems. The ideal candidate will have strong expertise in Scala, Spark, and Hadoop ecosystems, along with hands-on experience in building scalable data pipelines and distributed data processing applications. This role requires a strong analytical mindset, problem-solving ability, and passion for working with high-volume, high-velocity data environments. As a Big Data Engineer, you will be responsible for developing robust data solutions that support business intelligence, analytics, and data-driven decision-making across the organization. You will collaborate closely with data architects, data scientists, software engineers, and business stakeholders to deliver efficient and reliable data platforms. **Requirements** ### Key Responsibilities * Design, develop, and maintain scalable big data solutions using Scala, Apache Spark, and Hadoop technologies. * Build and optimize batch and real-time data processing pipelines for large datasets. * Develop reusable frameworks and components for data ingestion, transformation, validation, and storage. * Work extensively with distributed computing technologies such as HDFS, Yarn, Hive, and MapReduce. * Implement high-performance Spark applications and optimize data workflows for speed and scalability. * Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. * Monitor, troubleshoot, and enhance existing big data infrastructure and applications. * Ensure data quality, integrity, and consistency across multiple systems and platforms. * Participate in architecture discussions, code reviews, and technical documentation. * Support de
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