Description

Key Responsibilities:

• Design, develop, and maintain data solutions using Snowflake

• Write, optimize, and maintain complex SQL queries, views, stored procedures, and data transformation

processes

• Develop and maintain ETL/ELT pipelines to ingest and transform data from multiple sources

• Work with Snowflake features such as Snowpipe, Streams, Tasks, Time Travel, and Zero-Copy Cloning

• Monitor and optimize Snowflake queries and workloads for performance and cost efficiency

• Troubleshoot data pipeline issues and perform data validation to maintain data quality

• Collaborate with data scientists, analysts, and business teams to understand data requirements

• Perform data cleansing, preparation, transformation, and exploratory analysis

• Prepare datasets and develop data pipelines to support data science and machine learning initiatives

• Apply statistical and analytical techniques to identify patterns and generate insights

• Support feature engineering and data preparation for machine learning models

• Develop Python scripts for data processing, extraction, transformation, validation, and automation

• Build reusable utilities to streamline data engineering and data quality activities

• Automate repetitive data processing and validation tasks

• Integrate Python-based solutions with Snowflake and other data platforms

• Integrate Snowflake with databases, APIs, files, and other enterprise data sources

• Develop reliable data ingestion and integration processes using cloud platforms such as AWS, Azure, or

GCP

• Work with data orchestration and integration tools as required

• Ensure data accuracy, completeness, consistency, and reliability

• Follow established data security, governance, and access-control standards

• Maintain data documentation, metadata, and data lineage

• Collaborate with data engineers, data scientists, analysts, architects, and business stakeholders

• Participate in technical discussions, code reviews, testing, and troubleshooting

• Document data solutions, processes, and technical implementations

• Follow Agile development practices and contribute to continuous improvement initiatives

Required Skills:

• 5-10 years of experience in Data Engineering, Data Science, Analytics, or a related field

• Strong hands-on experience with Snowflake and its data engineering capabilities

• Strong proficiency in SQL, including complex query development and optimization

• Hands-on experience with Python for data processing and automation

• Experience designing, developing, and maintaining ETL/ELT pipelines

• Good understanding of data warehousing and data modelling concepts

• Experience working with at least one of AWS, Azure, or GCP

• Understanding of data cleansing, transformation, exploratory analysis, statistical analysis, and feature

engineering

• Understanding of data science, statistical analysis, and machine learning concepts

• Experience with Git or other version-control systems

• Strong analytical, troubleshooting, and problem-solving skills

• Good communication and collaboration skills

Preferred (Bonus) Skills:

• Snowflake certification, preferably SnowPro Core

• Experience with dbt, Apache Airflow, Azure Data Factory, Informatica, or Databricks

• Experience with Snowpark and Python

• Exposure to machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch

• Experience with data visualization tools such as Power BI or Tableau

Key Skills

Education

Bachelor's degree