We are looking for a skilled Data Engineer with expertise in SQL and Snowflake to join our data team. The ideal candidate should have 5+ years of experience working with data pipelines, ETL processes, and cloud-based data warehousing solutions. You will be responsible for building and optimizing data pipelines, ensuring data accuracy, and working with cross-functional teams to support various data-driven initiatives. The candidate should be proficient in designing data models and possess a deep understanding of best practices in data engineering.
Key Responsibilities:
Design and develop efficient data pipelines using SQL and Snowflake for data ingestion, transformation, and storage.
Build and maintain ETL processes to move large datasets from various sources into the data warehouse.
Work closely with data analysts and business stakeholders to understand data requirements and deliver appropriate solutions.
Create complex SQL queries and scripts for data analysis and reporting needs.
Optimize Snowflake database performance by implementing best practices for clustering, partitioning, and query tuning.
Ensure data accuracy and consistency by implementing robust validation and testing procedures.
Collaborate with the team to design and implement scalable data models that meet the needs of business stakeholders.
Monitor and troubleshoot data pipeline issues, ensuring high availability and reliability of the data platform.
Create and maintain technical documentation for data flows and processes.
Required Skills Qualifications:
5+ years of experience in data engineering, working with large-scale data systems.
Strong proficiency in SQL for data querying, analysis, and optimization.
Experience with Snowflake, including SnowSQL, data warehousing concepts, and performance optimization techniques.
Experience in building ETL pipelines using tools like Talend, Informatica, or Python-based ETL frameworks.
Understanding of data modeling techniques and best practices.
Proficiency with cloud platforms like AWS, Azure, or Google Cloud for data storage and management.
Experience in working with version control systems like Git.
Excellent problem-solving skills and ability to work independently and in a team.
Bachelor s degree in Computer Science, Information Systems, or related field preferred.
Experience with data orchestration tools like Apache Airflow.
Knowledge of Python or R for data manipulation and automation.
Familiarity with data visualization tools like Power BI or Tableau.
Understanding of DevOps and CI/CD practices in data engineering.
Experience with machine learning models and data science workflows.