Data engineer
2 months ago
Job Title: Data Engineer Location: Remote Job Summary: We are looking for a skilled Data Engineer to join our dynamic team.
The ideal candidate will have hands-on experience with Snowflake, data warehousing, data pipelines, and modern data engineering tools.
You will play a key role in designing, building, and maintaining our data infrastructure, ensuring high-quality data is available for analytics and decision-making.
Key Responsibilities: Design, develop, and maintain data pipelines to ensure the smooth flow of data into Snowflake and other data storage solutions.
Implement ETL processes using tools such as DBT and Apache Airflow for data transformation and orchestration.
Collaborate with data analysts and stakeholders to understand data requirements and deliver effective solutions.
Optimize and monitor data workflows to improve efficiency and performance.
Manage and maintain RDBMS databases, focusing on AWS RDS, ensuring data reliability and security.
Utilize Alteryx for data preparation and advanced analytics tasks as needed.
Ensure data quality and integrity by implementing best practices in data governance.
Document data architecture, processes, and workflows to support team knowledge sharing.
Qualifications: Bachelor’s degree in Computer Science, Information Technology, or a related field.
3+ years of experience in data engineering or related fields.
Strong proficiency in Snowflake, including experience with data modeling and performance optimization.
Experience in building and managing data pipelines using DBT and Apache Airflow.
Solid understanding of RDBMS principles and experience with AWS RDS.
Familiarity with data preparation and analytics using Alteryx.
Knowledge of cloud platforms, particularly AWS, including services such as S3, Event Bridge, and Lambda..
Excellent problem-solving skills and a proactive approach to challenges.
Strong communication skills, able to collaborate with technical and non-technical teams.
Preferred Skills: Experience with data visualization tools (e.g., Tableau, Power BI).
Familiarity with data warehousing concepts and methodologies.
Exposure to machine learning tools and frameworks is a plus.
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