Technical Architect

DataWeave · Bangalore

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Last observed by our collector: 8 October 2026 at 11:18 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: 05-202605141139-R

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Collected minimum qualification: Deep knowledge of data platforms and analytics architectures.Attendance and availability: I checked the employer page for work location, office attendance, start date and duration.Current requisition: I checked the current employer requisition and its application requirements.

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Collected role description

We, the Products team at DataWeave, build data products that provide timely insights that are readily consumable and actionable, at scale. Our underpinnings are: scale, impact, engagement, and visibility. We help businesses take data-driven decisions every day. We also give them insights into long-term strategy. We are focussed on creating value for our customers and helping them succeed. We are also responsible for creating and maintaining internal products and tools that help the rest of the organization scale. Our data science, data quality, CSM, and marketing teams use tools built by us. They are our internal customers. We are looking for a Technical Architect to lead the design and evolution of large-scale analytics and data-driven SaaS platforms. The role requires deep expertise in distributed systems, data engineering, and scalable architectures, with a strong focus on building systems that handle high-volume data processing, complex computations, and real-time analytics. The architect will work closely with engineering, data science, product, and platform teams to translate business requirements into robust, scalable, and cost-efficient technical solutions. Strong experience in distributed systems and SaaS system design. Deep knowledge of data platforms and analytics architectures. Expertise in at least some of: ○ Kafka / PubSub / Kinesis ○ Data lakes (S3/ADLS/GCS + Delta/Iceberg/Hudi). Columnar stores (Big Query, Redshift, Snowflake, ClickHouse) ○ MySQL, NoSQL (DynamoDB), Postgres, HBase, Spark Strong hands-on experience with AWS Proficient in creating technical documents like Architecture views, Technology Architecture blueprint and design specification Expertise in Containerization (Docker, Kubernetes) and knowledge of CI/CD and DevOps practices, monitoring and Alerting Tools like CloudWatch, DataDog, Sentry Strong coding background in: Python / Go Solid understanding of API design, Microservices architecture, Event-driven systems Solid understanding of Data modeling (OLAP, dimensional, event-based), Feature engineering, ML/LLM pipelines Experience building or supporting AI-powered analytics systems is a strong plus. Name Email Linkedin Resume Role Team Upload PDF or DOC files for resume. File size should not exceed 10 Mb. Apply Now

Collected minimum qualification

Deep knowledge of data platforms and analytics architectures.

Collected preferred qualification

Expertise in at least some of: ○ Kafka / PubSub / Kinesis ○ Data lakes (S3/ADLS/GCS + Delta/Iceberg/Hudi).