Data Analyst/Engineer

At Slyp, we're in the field of customer experience. We find it absurd that individuals can pay using a smartphone yet still get a paper receipt that's been around for centuries. Traditional receipts do nothing but inconvenience customers and, aside from serving as proof of purchase, offer no value to either retailers or consumers. We are committed to inventing top-tier technology and benefiting the environment, one receipt at a time. That's why we created the Slyp Smart Receipt. Why is Slyp a fantastic place to be employed? Slyp Village attracts high-caliber talent from across the world. Our accepting atmosphere empowers Slypsters to exhibit their creativity and ambition, while being a part of an initiative that's shaking things up for the better. Here are a few of our benefits: - Employee Stock Ownership Program (ESOP) - Generous Learning and Development program - $1500 budget every year for you to use towards perfecting your skill - Slyp Gives - we conduct 2 community give back days each year - Competitive leave policies including parental leave - Flexible work and the choice to work from anywhere globally for a certain period - Pet-friendly office, monthly lunch and learns (sometimes spontaneous), and a continuous team fun and experience program What we are seeking You should possess strong mathematical and numeracy skills and a solid understanding of SQL, ETL frameworks, and website scripts. You will work with and analyze data to predict and boost capabilities, construct data-driven products, and design and maintain essential data assets. You will assist with the design, implementation, and optimization of data pipelines. Your tasks will include creating new algorithm prototypes, presenting and visualizing data, collaborating with strategic partners, conducting statistical analysis, forecasting trends, and executing ad hoc analysis. You will also supply mathematical modeling and analysis abilities to support other business divisions. What does an ordinary day look like? Data Modeling and Analysis: - Use statistical analysis to extract valuable insights - Develop predictive models to enhance business processes and decision-making. - Expansion in machine learning is a plus Reporting and Visualization: - Design and maintain dashboards and reports for internal and external stakeholders - Communicate findings effectively to assist in directing business strategies Performance Optimization: - Continually optimize data pipelines for efficiency, scalability, and cost - Implement data engineering best practices to guarantee a robust and reliable infrastructure Data Quality Assurance: - Implement data quality checks and monitoring to ensure the data's precision and uniformity - Identify and fix data-related issues as they occur Data Integration: - Develop and maintain data pipelines to collect, cleanse, and arrange data from various sources Data Security: - Ensure compliance with data privacy and security standards and implement necessary safeguards What experience or knowledge will you add to the team? - Bachelor's or higher degree in Computer Science, Data Science, Information Systems, Economics, or a related field. - Familiarity with AWS data services (e.g., Glue, Redshift, Quicksight, Athena, S3, Sagemaker). - Additional knowledge of other AWS services is a bonus (e.g., Lambda, Kinesis, DMS, IAM, KMS). - Demonstrated experience in data engineering, including SQL, Python, ETL processes, and data modeling. - Experience in working with large datasets and data warehousing solutions. - Familiarity with machine learning techniques and tools is a plus. Additional experience or knowledge that would be helpful includes: - Previous experience in a similar role in the tech or fintech industry is a bonus. - Previous data analytics experience for the retail industry is highly valued. Our recruitment process 1. Screening phone call with our People Partner 2. Technical Interview with Senior Engineering Manager 3. Interview with Engineering and Data Leads 4. Final Interview with CTO and Co-Founder Requirements Due to our hybrid working model, we are currently not accepting applications for remote work. We are only considering candidates based in Sydney, NSW.