Amazon Workforce Solutions is looking to modernize one of its largest data warehouses to support business intelligence, data science, AI, and product management customers globally. The goal is to drive analytics and reporting by standardizing data platforms and automating data engineering.
Requirements
- 2+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
- 2+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience
- 2+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
- 5+ years of data engineering experience
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)
Responsibilities
- Designing, implementing, and supporting scalable solutions for metadata management, data pipeline orchestration, ETL, data modelling and data visualization with the best tools available from AWS – including Sage Maker Unified Studio, Redshift, Glue, S3, IAM, Cloudwatch, and Apache Airflow.
- Leading designs and deliver scalable ETL processes in the data lake platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making.
- Leading designs and delivering scalable ETL processes in the data lake platform to support rapidly growing and dynamic business demand.
- Processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution).
- Developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes).
- Leading and influencing the data or BI strategy of your team or organization.
- Implementing data governance practices, defining data access and quality standards and using AI to modernize analytics platforms.
Other
- Experience managing a data or BI team
- Experience communicating to senior management and customers verbally and in writing
- Excellent business and communication skills to collaborate with business owners, product teams, data science teams and technical leaders to gather infrastructure requirements, design data infrastructure, and build data pipelines and datasets to meet business needs.
- Excellent business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting, analytics and science projects.
- Lead a team of Data Engineers and Business Intelligence Engineers solving problems for Workforce Solutions customers.
