Senior Data Engineer Job in Bengaluru at Kula

Kula is hiring for the role of Data Engineer!

Responsibilities of the Candidate:

• Build and scale real-time and batch data pipelines capable of supporting high-volume data ingestion and processing.
• Power diverse applications across: business logic and personalization, user cohorting and CRM, product and business analytics, and Generative AI (data retrieval, prompt engineering, context feeding).
• Partner with product analysts to co-design analytics schemas that align across all client platforms.
• Enable consistent event tracking and unified user behavior analysis.
• Ensure availability of enriched and aggregated datasets that can be plugged directly into product and business workflows
• Own the entire lifecycle of the data platform — from design and provisioning to resource decommissioning.
• Implement systems for:
• Dynamic resource allocation (compute, storage, streaming)
• Tiered data retention and archival
• Usage-based cost governance and alerting
• Develop tooling, playbooks, and dashboards for observability, efficiency, and compliance.
• Build proactive monitoring and alerting for data freshness, volume anomalies, and schema drift.
• Conduct root cause analyses (RCA) for failures or inconsistencies across systems.
• Define and enforce role-based access control (RBAC) and audit policies for secure data operations.
• Maintain thorough documentation of data flows, architecture, and contracts.

Requirements:

• Experience building cloud-native data solutions on AWS (RDS, Redshift, Athena, Kinesis, Lambda, S3) and GCP (BigQuery, Dataflow, Datastream).
• Proficiency in SQL, NoSQL, and data modeling for both OLTP and OLAP systems.
• Strong backend engineering skills using Golang (preferred) or other typed languages.
• Hands-on experience with event streaming platforms like Kafka, Kinesis, or RabbitMQ.
• Deep understanding of data warehousing, pipeline orchestration, and cloud architecture.
• Demonstrated ability to implement secure, auditable, and scalable data governance frameworks.
• Scripting expertise in Bash or Python for automation.
• Familiarity with Apache Spark, Flink, or other big data processing engines.
• Experience with CI/CD, Infrastructure-as-Code (Terraform, CloudFormation), and deployment automation.
• Experience designing datasets and platforms that support both BI and machine learning workloads.