Required Skills:
- AWS Data Services
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Data Pipelines / ETL
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Python
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SQL / Data Warehousing
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DevSecOps / CI/CD
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Git / Linux
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Data Integration Testing
Nice to Have:
- Performance Optimization
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BI / Analytics
• Design and develop new features based on consumer application requests to ingest data in the different layers of IntelDS. • Automate the integration and delivery of data objects and data pipelines. Direct reports • Not applicable Duties and responsibilities The duties and responsibilities of this job are to prepare data and make it available in an efficient and optimized format for our different data consumers, ranging from BI and analytics to data science applications. It requires to work with current technologies used by IntelDS and in particular Apache Spark, Lambda & Step Functions, Glue Data Catalog, and RedShift on AWS environment. This includes: • Design and develop new data ingestion patterns into IntelDS Raw and/or Unified data layers based on the requirements and needs for connecting new data sources or for building new data objects. Working in ingestion patterns allow to automate the data pipelines. • Participate to and apply DevSecOps practices by automating the integration and delivery of data pipelines in a cloud environment. This can include the design and implementation of end-to-end data integration tests and/or CICD pipelines. • Analyse existing data models, identify and implement performance optimizations for data ingestion and data consumption. The objective is to accelerate data availability within the platform and to consumer applications. • Support client applications in connecting and consuming data from the platform, and ensure they follow our guidelines and best practices. • Participate in the monitoring of the platform and debugging of detected issues and bugs. Qualifications Minimum of 3 years prior experience as data engineer with proven experience on Big Data and Data Lakes on a cloud environment. Bachelor or Master degree in computer science or applied mathematics (or equivalent). Qualifications include: • Proven experience working with data pipelines / ETL / BI regardless of the technology. • Proven experience working with AWS including at least 3 of: RedShift, S3, EMR, Cloud Formation, DynamoDB, RDS, lambda. • Big Data technologies and distributed systems: one of Spark, Presto or Hive. • Python language: scripting and object oriented. • Fluency in SQL for datawarehousing (RedShift in particular is a plus). • Good undesrtanding on datawarehousing and Data modelling concepts • Familiar with GIT, Linux, CI/CD pipelines is a plus. • Strong systems/process orientation with demonstrated analytical thinking, organization skills and problem-solving skills. • Ability to self-manage, prioritize and execute tasks in a demanding environment. • Strong consultancy orientation and experience, with the ability to form collaborative, productive working relationships across diverse teams and cultures is a must. • Willingness and ability to train and teach others. • Proven experience working with data pipelines / ETL / BI regardless of the technology. • Proven experience working with AWS including at least 3 of: RedShift, S3, EMR, Cloud Formation, DynamoDB, RDS, lambda. • Big Data technologies and distributed systems: one of Spark, Presto or Hive. • Python language: scripting and object oriented. • Fluency in SQL for datawarehousing (RedShift in particular is a plus). • Good undesrtanding on datawarehousing and Data modelling concepts • Familiar with GIT, Linux, CI/CD pipelines is a plus.
