Technical Architect
DataWeave · Bangalore
Collected role description
Role overview
Technical Architect at DataWeave
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.
Employment details
- Location: Bangalore [India]
Application details
- Apply Now
About the employer
- We, the Products team at DataWeave, build data products that provide timely insights that are readily consumable and actionable, at scale.
Additional role details
- 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 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.
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).