Data Engineer (Pentaho)

Requirement: Data Engineer

CDS Global is looking for a Data Engineer to work on a significant data pipeline and data warehouse that supports analytics, consumer marketing, data science, and data products across Hearst Magazines and CDS Global’s Resin platform. As a Data Engineer, you will develop data pipelines and a consumer marketing database that will be used across Hearst. You will leverage a modern data stack, with a particular focus across Amazon Web Services (AWS), Pentaho, Apache Airflow, and Looker, powering a variety of ETL and reverse ETL processes, customer segmentation and activation, and insights. And you will have the opportunity to play a critical part in the digital transformation of a world-leading media company. You will:

1. Work with an established data engineering team within an Agile/SCRUM development environment.
2. Architect, write code, and perform testing and debugging of Hearst and CDS Global’s data infrastructure.
3. Help build out the new Data Lake and ETL infrastructure, and migrate from the existing setup to the new..
4. Build data APIs and data delivery services that support critical operational and analytical applications for our business operations, customers and partners.
5. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
6. Leverage the resources of a successful, well-known business combined with the nimbleness and forward-looking feel of a startup. You have: Experience with cloud data infrastructure and data orchestration tools, in particular AWS, Pentaho, Postgres and MySQL, and Apache Airflow.
7. Deep understanding in Data warehousing space and AWS data services like RDS, Redshift, S3, MWAA, Athena and Glue.
8. Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
9. Expert knowledge Pentaho and other modern AWS ETL tools.
10. Experience in managing and migrating databases in the range of multiple terabytes.
11. Deep knowledge in Airflow.
12. Strong fluency with Python and SQL, and experience working with relational databases, query authoring, as well as familiarity with a variety of databases.
13. Hands-on expertise with SQL and SQL analytics.
14. Experience working with code repositories like github.
15. Strong analytical skills related to working with unstructured datasets.
16. Experience supporting and working with cross-functional teams in a dynamic environment.
17. Experience in Big data technologies like Apache Spark is a huge plus.
18. 5+ years of experience in a Data Engineer role, with B.S./M.S. in Computer Science or a related field, or equivalent experience.
19. Experience working with offshore teams - coordinating/managing offshore resources.