SE II Data Engineer (Contract) - 6 Months
Pune, Maharashtra, India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Contract — employment source
Employment type in the employer’s listing: Contract
From the employer’s posting
What you’ll work on
Full postingBuild scalable data pipelines inside Snowflake using Snowpark and stored procedures
Embed Snowflake Cortex LLM features like summarization and anomaly detection into data workflows
Tune Snowflake compute cost and query performance, especially for LLM and agentic functions
Build Streamlit data products that surface GenAI insights to business users
Design clean, secure data schemas for analytics and AI/ML workloads
From the employer’s posting
Design, build, and deploy highly scalable data pipelines natively within Snowflake using Snowpark and Python/SQL Stored Procedures.
embedding LLM capabilities (summarization, anomaly detection, automated insights) directly into core data workflows
Rigorously monitor, troubleshoot, and optimize Snowflake compute costs and query performance
Rapidly prototype, build, and deploy intelligent, interactive data products and internal tools using Streamlit
Apply expert-level data modeling practices to design clean, scalable, and secure data schemas
What you’ll bring
All qualificationsCore experience
- 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.
- Communication: Strong verbal and written communication skills, with the ability to translate complex AI/data concepts to business stakeholders efficiently.
Qualification wording
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.
Communication: Strong verbal and written communication skills, with the ability to translate complex AI/data concepts to business stakeholders efficiently.
Education & alternatives
- 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.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- GCP
- Kafka
- Snowflake
- Airflow
- Dagster
- Streamlit
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- 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).
- 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.
- 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.
- 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 internal tools using Streamlit to surface GenAI insights to business users.
- Cross-Functional Collaboration: Collaborate closely with product managers, analytics teams, and business stakeholders to translate requirements into robust, AI-powered technical solutions. - Engineering Standards: Maintain high engineering standards by writing clear technical design documents, conducting thorough code reviews, and implementing CI/CD best practices for Snowflake artifacts. Benefits
- 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.
- 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 internal tools using Streamlit to surface GenAI insights to business users. - Data Modeling & Architecture: Apply expert-level data modeling practices to design clean, scalable, and secure data schemas that support both traditional analytics and complex AI/ML workloads.
Benefits in the posting
Full benefits wording- Hybrid setup
- Worker's insurance
- Paid Time Offs
From the employer’s posting.
Posting record
Report an errorOpen 4 monthsWe first saw this listing 123 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 23, 2026 · 123 days ago
- Recorded sightings
- 276
- Last seen by us
- Oct 24, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job 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 internal tools using Streamlit to surface GenAI insights to business users.
Data Modeling & Architecture: Apply expert-level data modeling practices to design clean, scalable, and secure data schemas that support both traditional analytics and complex AI/ML workloads.
Rapid Iteration & Delivery: Operate effectively in a fast-paced contract environment, owning end-to-end technical delivery from architecture to deployment, and hitting the ground running to solve immediate business challenges.
Cross-Functional Collaboration: Collaborate closely with product managers, analytics teams, and business stakeholders to translate requirements into robust, AI-powered technical solutions.
Engineering Standards: Maintain high engineering standards by writing clear technical design documents, conducting thorough code reviews, and implementing CI/CD best practices for Snowflake artifacts.
Benefits
- Hybrid setup
- Worker's insurance
- Paid Time Offs
- Other employee benefits to be discussed by our Talent Acquisition team in India.
Helpshift embraces diversity. We are proud to be an equal opportunity workplace and do not discriminate on the basis of sex, race, color, age, sexual orientation, gender identity, religion, national origin, citizenship, marital status, veteran status, or disability status
Privacy Notice
By providing your information in this application, you understand that we will collect and process your information in accordance with our Applicant Privacy Notice. For more information, please see our Applicant Privacy Notice at .
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- Pay
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- Location & working pattern
Pune, Maharashtra, India
Benefits - Hybrid setup - Worker's insurance
- Work authorization
- Other employee benefits to be discussed by our Talent Acquisition team in India. Helpshift embraces diversity. We are proud to be an equal opportunity workplace and do not discriminate on the basis of sex, race, color, age, sexual orientation, gender identity, religion, national origin, citizenship, marital status, veteran status, or disability status Privacy Notice By providing your information in this application, you understand that we will collect and process your information in accordance with our Applicant Privacy Notice. For more information, please see our Applicant Privacy Notice at .
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