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ChargePoint, Pvt. Ltd.
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Staff Data Engineer

Staff Data Engineer

ChargePoint, Pvt. Ltd.

6 - 10 years

13 - 17 Lacs

Bengaluru

Posted:4 months ago| Platform:

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Skills Required

Analytical Machine learning Director Agile Application development Data quality Natural language processing Monitoring Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

As a Staff Data Engineer at ChargePoint , you will play a crucial role in designing, building, and maintaining our data infrastructure. You will collaborate closely with cross-functional teams to ensure the availability and reliability of data for various analytical and reporting needs. If you are passionate about data engineering, excited to tackle challenges, and have a strong background in developing robust data pipelines, we want to hear from you.

What You Will Bring to ChargePoint:

Data Pipeline Development: Design, build, and optimize data pipelines to ensure the efficient and scalable flow of data from source to destination.
Problem Solving: Demonstrate strong problem-solving and logical reasoning skills to address complex data engineering challenges.
Team Collaboration: Collaborate effectively with cross-functional teams and be a proactive team player.
Programming: Utilize your programming skills to develop and maintain data pipelines, focusing on reliability and performance.
Agile Environment: Thrive in an agile work environment, adapting to changing requirements and priorities.
Python: Leverage your proficiency in Python programming to develop data solutions.
NLP Understanding: Demonstrate an understanding of Natural Language Processing (NLP) algorithms and the ability to implement them.
AWS Stack: Possess strong experience with the AWS data stack, including services like [list relevant AWS services].
Big Data Technologies: Hands-on experience with PySpark, Apache Spark, and CI/CD implementation using Terraform.
Snowflake and dbt: Experience in building ELT pipelines using Snowflake and dbt.
BI Tools: Familiarity with BI tools such as PowerBI OR Tableau for data visualization and reporting.
Data Quality: Understand the importance of data quality and proactively work towards building high-quality data pipelines.
Machine Learning Application Development: Collaborate with data scientists and MLOps teams to design and implement production-grade machine learning models using both traditional ML and Generative AI techniques.
Model Deployment and Monitoring: Build end-to-end pipelines for training, deploying, and monitoring ML models, ensuring reliability and scalability.
Generative AI Integration: Develop applications leveraging LLMs (eg, OpenAI, Hugging Face models) for tasks such as summarization, classification, recommendation, and conversational AI.

Requirements:

- Bachelors or Masters degree in Computer Science, Data Science, or a related field.
- Proven experience in data engineering with 6-10 years in a similar role.
- Strong problem-solving skills and logical reasoning.
- Proficiency in Python programming.
- Knowledge of NLP algorithms and their implementation.
- Experience with the AWS data stack.
- Hands-on experience with PySpark, Apache Spark, and CI/CD using Terraform.
- Familiarity with Snowflake and dbt for ELT pipelines.
- Experience with BI tools like PowerBI and Tableau.
- Strong understanding of data quality best practices.
- Hands-on experience building and deploying ML models using scikit-learn, XGBoost, TensorFlow or PyTorch.
- Proficiency with MLOps practices and tools (eg, MLflow, SageMaker, Vertex AI, Kubeflow, or similar).
- Experience working with or fine-tuning LLMs or transformer-based models (eg, GPT, BERT).
- Familiarity with vector databases (eg, FAISS, Pinecone) and prompt engineering for Generative AI applications

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Staff Data Engineer