SE II Data Engineer (Contract) - 6 Months
Keywords Studios
| Company | Keywords Studios |
| Category | Engineering |
| Location | Pune |
| Remote | On-site (inferred) |
| Employment | Contract |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 23 Jun 2026 |
| Last verified | 5 Aug 2026 |
| Source | Employer ATS (workable) |
Description
We are on a mission to rid the world of bad customer service by “mobilizing” the way help is delivered. Today’s consumers want an always-available customer service experience that leaves them feeling valued and respected. Helpshift helps B2B brands deliver this modern customer service experience through a mobile-first approach. We have changed how conversations take place, moving the conversation away from a slow, outdated email and desktop experience to an in-app chat experience that allows users to interact with brands in their own time. Through our market-leading AI-powered chatbots and automation, we help brands deliver instant and rapid resolutions. Because agents play a key role in delivering help, our platform gives agents superpowers with automation and AI that simply works. Companies such as Scopely, Supercell, Brex, EA, Square along with hundreds of other leading brands use the Helpshift platform to mobilize customer service delivery. Over 900 million active monthly consumers are enabled on 2B+ devices worldwide with Helpshift. Some numbers that illustrate our scale: 85k/rps 30ms response time 300 GB data transfer/hour 1000 VMs deployed at peak Requirements Requirements Experience: 5+ years of Data Engineering experience, with a proven track record of building complex, high-performance data pipelines and AI-driven systems in production environments. Deep Snowflake Expertise: Extensive, hands-on professional experience with Snowflake, including advanced data modeling, schema design, and native Snowflake features. Programming Mastery: Expert-level proficiency in Python and SQL, with strong foundational knowledge in data structures, algorithms, and software engineering best practices. Snowflake Cortex & GenAI: Demonstrable experience leveraging Snowflake Cortex AI to build scalable GenAI and Agentic use-cases directly within the data platform. Advanced Data Pipelines: Extensive experience designing and implementing complex, automated data pipelines utilizing Snowflake Stored Procedures (Snowpark Python/SQL). LLM Cost & Performance Optimization: Deep understanding of performance tuning and cost optimization specifically tailored for LLMs, vector searches, and Agentic systems running within cloud data platforms. Data Products via Streamlit: Hands-on experience building, deploying, and optimizing interactive data applications and user interfaces using Streamlit. Cloud Infrastructure: Familiarity with modern cloud platforms (AWS/GCP/Azure) and their integration with Snowflake data infrastructure. System Operations: Solid understanding of production system operations, including observability, data quality monitoring, reliability, and Snowflake security/RBAC. Bonus Skills: Experience with modern orchestrators (e.g., Airflow, Dagster), streaming data (Kafka, Snowpipe Streaming), or traditional BI tools is a plus, but secondary to Snowpark/Cortex expertise. Education: Bachelor’s Degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Communication: Strong verbal and written communication skills, with the ability to translate complex AI/data concepts to business stakeholders efficiently. Responsibilities Cortex & Agentic Architecture: Architect and implement advanced Agentic use-cases leveraging Snowflake Cortex, embedding LLM capabilities (summarization, anomaly detection, automated insights) directly into core data workflows. Complex Pipeline Development: Design, build, and deploy highly scalable data pipelines natively within Snowflake using Snowpark and Python/SQL Stored Procedures. Cost & Performance Optimization: Rigorously monitor, troubleshoot, and optimize Snowflake compute costs and query performance, specifically focusing on the execution efficiency of LLMs and Agentic functions. Streamlit Application Delivery: Rapidly prototype, build, and deploy intelligent, interactive data products and int