Data Engineer/ Machine Learning Engineer
2 weeks ago
Job Title: Data Engineer / Machine Learning Engineer (Snowflake, Python, ETL)
Location: chennai, Mumbai, Ahmedabad
Type: [Full-time]
Department: Data Engineering / AI & ML.
Job Summary:
We are looking for a skilled and motivated Data Engineer / Machine Learning Engineer with expertise in Snowflake, Python, ETL processes, and Machine Learning to join our growing data team. You will be responsible for designing and building data pipelines, enabling machine learning workflows, and optimizing data storage and processing within Snowflake.
Key Responsibilities:
- Design, develop, and maintain robust ETL/ELT pipelines to move and transform data across systems using Python and SQL.
- Implement and optimize data models in Snowflake to support analytics, reporting, and machine learning use cases.
- Build and deploy machine learning models into production pipelines and monitor their performance.
- Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver actionable insights.
- Ensure data quality, integrity, and governance across data pipelines and storage.
- Automate data workflows and contribute to the continuous improvement of the data platform.
- Participate in performance tuning, monitoring, and troubleshooting Snowflake environments.
Required Skills & Qualifications:
- 5+ years of experience in data engineering or ML engineering roles.
- Strong programming skills in Python, with experience in data manipulation libraries (e.g., Pandas, NumPy).
- Expertise in Snowflake: data warehousing concepts, query performance tuning, SnowSQL, and UDFs.
- Proficiency in building and maintaining ETL/ELT pipelines using tools like Airflow, DBT, or custom Python-based pipelines.
- Experience in deploying and managing machine learning models in production.
- Solid understanding of SQL and database optimization techniques.
- Familiarity with version control tools (e.g., Git) and CI/CD pipelines.
- Experience with cloud platforms like AWS, GCP, or Azure (preferred).
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