Technical Architect

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.
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