Senior Data Engineer

The ideal candidate will use their passion for big data and analytics to provide insights to the business covering a range of topics. They will be responsible for conducting both recurring and ad hoc analysis for business users. As a Data Engineer, you will play a critical role in the development and maintenance of our data infrastructure. You will work closely with cross-functional teams to ensure data availability, quality, and accessibility for analysis.

Position Outputs / Competencies

• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
• Design, develop, and maintain data pipelines and ETL processes.
• Implement and maintain data warehousing and data storage solutions.
• Optimize data pipelines for performance, scalability, and reliability.
• Ensure data quality and integrity through data validation and cleansing processes.
• Monitor and troubleshoot data infrastructure issues.
• Stay current with emerging technologies and best practices in data engineering.
• Systematic solution design of the ETL and data pipeline in line with business user specifications.
• Develop and implement ETL pipelines aligned to the approved solution design.
• Ensure data governance and data quality assurance standards are upheld.
• Deal with customers in a customer-centric manner.
• Effective self-management and teamwork.

Minimum Qualification and Experience

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Proven experience as a Data Engineer in a professional setting.
• Proficiency in data engineering technologies and programming languages (e.g., SQL, Python, Scala, Java).
• Strong knowledge of data storage, database design, and data modeling concepts.
• Experience with ETL tools, data integration, and data pipeline orchestration.
• Familiarity with data warehousing solutions (e.g., Snowflake, Redshift).
• Excellent problem-solving and troubleshooting skills.
• Strong communication and collaboration skills.
• 5-10 years of experience and understanding in designing and developing data warehouses according to the Kimball methodology.
• Adept at design and development of ETL processes.
• SQL development experience, preferably SAS data studio and AWS experience. The ability to ingest/output CSV, JSON, and other flat file types and any related data sources.
• Proficient in Python or R or willingness to learn. Experience within retail, financial services, and logistics environments.
• Understanding of data security and compliance best practices.
• Relevant certifications (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer).