Data Engineer

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. They are seeking an experienced Data Engineer to enhance their data pipelines, streamline their data warehouse, and support machine learning applications to drive business value.

Responsibilities:

• Design, develop, and maintain scalable and reliable data pipelines using modern data engineering tools and technologies
• Help drive the re-architecture of our data warehouse to improve performance, scalability, and data quality
• Implement data cleansing, transformation, and validation processes to ensure data accuracy and consistency
• Collaborate with other engineers and stakeholders to define data requirements and develop data models
• Build and maintain data infrastructure on GCP, including data lakes, data warehouses, and data pipelines
• Optimize data storage and retrieval for performance and cost efficiency
• Monitor data pipeline performance and troubleshoot issues
• Implement data security and governance best practices
• Prepare and transform data for machine learning models, ensuring data quality and consistency
• Enable data access for machine learning algorithms and tools
• Assist with basic data analysis and reporting tasks to support the AI team
• Work with the engineering team to support ML models
• Work closely with engineers, data scientists, and product managers to understand data needs and deliver solutions
• Document data pipelines and data models for knowledge sharing and maintainability
• Communicate effectively with team members and stakeholders
• Provide technical guidance and mentorship to the data team
• Foster a culture of innovation and collaboration within the data team
• Collaborate with cross-functional teams to integrate ML solutions into the Stord platform
• Drive data democratization and promote data-driven decision-making

Requirements:

• 5+ years of experience in data engineering or a related field
• Proven experience building and maintaining data pipelines and data warehouses
• Experience with cloud platforms, preferably GCP
• Experience with SQL and data modeling
• Experience with data transformation tools such as dbt, or similar
• Strong proficiency in SQL and Python
• Experience with data pipeline tools (e.g., Apache Airflow, Prefect, or similar)
• Experience with data warehousing technologies (e.g., BigQuery, Snowflake)
• Familiarity with data lake concepts and technologies
• Understanding of data engineering best practices
• Understanding of basic machine learning concepts, data preparation techniques, and model evaluation
• Experience with version control systems (e.g., Git)
• Strong problem-solving and analytical skills
• Excellent communication and collaboration skills
• Ability to work independently and as part of a team
• Strong attention to detail
• Basic understanding of data science concepts, including common machine learning models and statistical analysis
• Experience with machine learning data preparation
• Experience in the logistics or supply chain industry
• Experience in a startup environment