- Bachelor’s degree in computer science, Data Science, engineering, mathematics, information systems, or a related technical discipline
- 5+ years of relevant experience in data engineering roles
- 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
An AWS Data Engineer is responsible for designing, building, and maintaining the data infrastructure for an organization using AWS cloud services. This includes creating data pipelines, integrating data from various sources, and implementing data security and privacy measures. The AWS Data Engineer will also be responsible for monitoring and troubleshooting data flows and optimizing data storage and processing for performance and cost efficiency.
Preferred Skills
- Master’s degree in computer science, Data Science, engineering, mathematics, information systems, or a related technical discipline
- 5+ years of work experience with ETL, Data Modelling, and Data Architecture.
- 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