Data Platform/Platform Engineer (2-4 Years Experience)

Job Description

About the Role We are seeking an ambitious and experienced Data Platform/Platform Engineer to join our team in Bangalore. This role is ideal for a hands-on engineer with 2-4 years of experience who possesses a strong foundation in core software engineering, a "Data + Infra" hybrid mindset, and the drive to thrive in a fast-paced, autonomous environment. You will be critical in designing, building, and maintaining our cloud-native data platform and spearheading the development of our internal Analytics AI Agent. Qualification and Experience The "Must-Haves" Experience: 2+ years of core Software Engineering experience with a "Data + Infra" hybrid mindset (e.g., Data Platform, SRE, or Platform Engineering background). Tech Stack: Strong proficiency in at least one of the following: Python, Go, or Java . Deep familiarity with Postgres is required. Cloud Native: Hands-on experience with a major Public Cloud provider ( AWS, GCP, or Azure ) and significant experience with Container Orchestration (Kubernetes) . Mindset: Possess a "Startup DNA" ?a proven ability to thrive in ambiguity, iterate rapidly, and execute with autonomy. The "Good-to-Haves" Data Stack: Exposure to Dimensional Modelling , Big Data technologies (e.g., Spark, Athena, Parquet), or NoSQL stores (e.g., Clickhouse, MongoDB). Advanced Engineering: Experience working with streaming frameworks (e.g., Flink, Spark Streaming) or advanced data orchestration tools ( Airflow ). GenAI: Experience building tools or applications using LLM APIs (e.g., OpenAI, Anthropic) and frameworks like Haystack/LangChain/LlamaIndex . Roles and Responsibilities Analytics AI Agent & BI as Code: Spearhead the development and implementation of the internal Analytics AI Agent and semantic layer to enable natural language data interaction. Drive the transition of the organization to version-controlled, reproducible metrics ("BI as Code"). Platform Engineering: Design, build, and maintain the cloud-native infrastructure (leveraging Kubernetes, AWS/GCP) that powers our Data Platform. Scale & Reliability: Architect robust, fault-tolerant batch and streaming data applications, ensuring high availability and performance. Technical Product Ownership: Act as a technical product owner for data/infra solutions, identifying stakeholder friction points and solving them via software solutions rather than just process, ultimately reducing "Time to Insight." Culture of Excellence: Drive and advocate for best practices in CI/CD, observability, and system design. Mentor and support junior engineers in their professional development.