Weekday AI
BigDataDeveloper
Neural analysis suggests this role is
optimal for Mid candidates.
“Big Data Developer at Weekday AI. Skills: Big Data Development, Data Engineering, Scalable Data Pipelines, Data Processing Systems, AWS Cloud Services, PostgreSQL, Distributed Systems, ETL/ELT. Design, develop, and maintain scalable data pipelines and big data processing systems. Build and optimize data architectures using AWS services for high availability and performance”
What You'll Achieve.
deliver high-performance data solutions that support critical decision-making; play an important role in shaping the data infrastructure, improving performance, and enabling data-driven innovation across the organization
Industry & Context.
problem-solving and analytical skills
What They're Looking For.
Must Have
4+ years of experience in big data development, data engineering, or related roles, hands-on experience with AWS cloud services for data processing and storage, Expertise in PostgreSQL including query optimization and database design, Experience working with large-scale datasets and distributed systems, Proficiency in building efficient ETL pipelines and data workflows, Ability to work in fast-paced environments and manage multiple priorities
Nice to Have
Apache Spark (good to have), Familiarity with Apache Spark and big data processing frameworks, Exposure to on-premise data environments and hybrid architectures is a plus
What You'll Do.
and maintain scalable data pipelines and big data processing systems
Build and optimize data architectures using AWS services for high availability and performance
Work with PostgreSQL for data storage
and performance tuning
Process and analyze large datasets efficiently to support analytics and reporting needs
and security across all data systems
Optimize data workflows for performance
Implement ETL/ELT processes for seamless data ingestion and transformation
Monitor and troubleshoot data pipelines to ensure reliability and uptime
Support hybrid environments by integrating cloud and on-premise data systems
Document data architecture
and best practices for future scalability
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams to understand data requirements and deliver solutions; ability to collaborate with technical and non-technical teams
Communication Scope
Good communication skills
Process & Methodology
manage multiple priorities
Full Job Description
**This role is for one of the Weekday's clients** **Salary range: Rs 500000 - Rs 2000000 (ie INR 5-20 LPA)** Min Experience: 4 years Location: Mumbai, Bangalore JobType: full-time We are looking for a skilled Big Data Developer to design, build, and optimize scalable data pipelines and data processing systems that power business intelligence and advanced analytics. This role focuses on handling large-scale structured and unstructured data, ensuring efficient data flow, storage, and accessibility across cloud and on-premise environments. You will work closely with data engineers, analysts, and product teams to deliver high-performance data solutions that support critical decision-making. The position requires strong expertise in cloud-based architectures, database management, and distributed data processing, along with the ability to build reliable, secure, and scalable systems. As a key contributor, you will play an important role in shaping the data infrastructure, improving performance, and enabling data-driven innovation across the organization. **Requirements** **Key Responsibilities** * Design, develop, and maintain scalable data pipelines and big data processing systems * Build and optimize data architectures using AWS services for high availability and performance * Work with PostgreSQL for data storage, querying, and performance tuning * Process and analyze large datasets efficiently to support analytics and reporting needs * Collaborate with cross-functional teams to understand data requirements and deliver solutions * Ensure data quality, integrity, and security across all data systems * Optimize data workflows for performance, scalability, and cost efficiency * Implement ETL/ELT processes for seamless data ingestion and transformation * Monitor and troubleshoot data pipelines to ensure reliability and uptime * Work with distributed processing frameworks like Apache Spark (good to have) * Support hybrid environments by integrating cloud and on-premise data
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