Principal Data Engineer, Aerospike

• Experience: 5-7 years in data architecture, data engineering, business intelligence, or a related field, with a proven track record of designing and implementing data infrastructures and analytics solutions
• Technical Skills: Experience with data warehousing solutions such as Snowflake, AWS Redshift, or Google BigQuery. Familiarity with ETL tools and programming languages like Python
• Data Modeling and Design: Strong understanding of data modeling techniques and methodologies, with experience in designing and implementing database models and schemas
• Analytical Skills: Ability to analyze complex datasets and translate findings into actionable business insights
• BI Tools: Experience with BI and data visualization tools such as Tableau, Power BI, or Looker
• Data Governance Knowledge: Understanding of data governance practices, data security standards, and compliance requirements
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders
• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field

Desirable

• We are seeking a talented and versatile professional to lead the development of our data infrastructure, strategy, and analytics capabilities, driving data-informed decision-making across the organization
• As the company’s first Data Engineer, you will have a unique opportunity to establish and shape the Data Strategy & Analytics function, building from the ground up to support the company’s growth and global operations
• Data Strategy Development: Define and implement a data strategy that aligns with business objectives, ensuring data initiatives support organizational goals
• Data Architecture Design: Create and manage the company’s data architecture, including data models, database structures, and data flow diagrams, to ensure efficient data management and accessibility
• Data Integration and Pipeline Construction: Develop and maintain robust data pipelines to extract, transform, and load (ETL) data from various sources into centralized repositories, ensuring seamless data flow and integration
• Data Governance Implementation: Establish and enforce data governance practices to ensure data quality, security, and compliance with relevant regulations
• Business Intelligence and Reporting: Develop and maintain BI solutions, including dashboards and reports, to present insights to stakeholders and support data-driven decision-making
• Collaboration: Work closely with cross-functional teams, including product, marketing, and finance, to understand data needs and deliver actionable insights
• Data Quality Assurance: Monitor and optimize data systems to ensure performance, scalability, and integrity, maintaining high standards of data quality and reliability