About this role
• Bachelor’s degree in computer science, Data Science, engineering, mathematics, information systems, or a related technical discipline
• 7+ years of relevant experience in data engineering roles with primary skills on Databricks on AWS
• Detailed knowledge of data warehouse technical architectures, data modelling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
• Proficient in at least one or more programming languages: Java, Python, Ruby, Scala
• Experienced with AWS services such as Redshift, S3, EC2, Lambda, Athena, EMR, AWS Glue, Datapipeline.
• Exposure to data visualization and reporting with tools such as Amazon QuickSight, Metabase, Tableau, or similar software
• Experience building metrics deck and dashboards for KPIs including the underlying data models.
• Understand how to design, implement, and maintain a platform providing secured access to large datasets
• Master’s degree in computer science, Data Science, engineering, mathematics, information systems, or a related technical discipline
• 7+ years of work experience with ETL, Data Modelling, and Data Architecture with primary skills on Databricks on AWS .
• Experience or familiarity with newer analytics tools such as AWS Lake Formation, Sagemaker, DynamoDB, Lambda, ElasticSearch.
• Experience with Data streaming service e.g Kinesis Kafka
• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
• Proven track record partnering with business owners to understand requirements and developing analysis to solve their business problems
• Proven analytical and quantitative ability and a passion for enabling customers to use data and metrics to back up assumptions, develop business cases, and complete root cause analysis
• Bachelor’s or higher degree in Computer Science or a related discipline; or equivalent (minimum 10+ years work experience).