Cloud Data Engineer - Snowflake - Hybrid
We are working in partnership with one of our largest customers who are a massive global player in the Pharmaceutical Manufacturing sector.
Essential Skills
1. Excellent experience in AWS data engineering ecosystem: SNS, SQS, Lambda, Glue, S3, EMR, log management, AWS containers, EC2, EBS, control access, data streaming, AWS CLI & SDK, backup & restore, etc.
2. Excellent experience in Object-Oriented programming (Java, Python, C#), Airflow, Apache Spark, source control (GIT) & versioning.
3. Excellent experience in Snowflake tools and services.
4. A strong understanding of databases and advanced SQL skills.
5. Experience of designing self-service data management capabilities: Auto ingestion, data cataloguing, automated access control, life cycle management, backup & restore, etc.
6. Experience working in software engineering CI/CD processes, with experience in the design and implementation of applications automated test, build, release, deployment, containerization, and configuration control management.
7. Proven record of design, implementation, and performance tuning of large-scale data pipelines using any ETL & orchestration tools: Talend, Informatica, Airflow, etc.
8. Experience of semi-structured (XML, JSON) and unstructured data handling including extraction and ingestion via web-scraping and FTP/SFTP.
9. Experience working with JIRA and Service Now.
10. Experience of delivering solutions through Agile and SAFe.
Key Accountabilities
1. Collaborate in the design and implementation of capabilities such as data share & collaboration environment, auto ingestion, data cataloguing, automated access control, life cycle management, backup & restore, etc.
2. Analyse data requirements, source data, model the source, and suggest the best methods & tech stack for extracting, transforming, and loading the data into the data platform and processing the data through the layers of the data platform.
3. Implementation of optimal ETL workflows from a wide variety of data sources using SQL, APIs, ETL tools, & AWS big data technologies.
4. Liaise with technical infrastructure teams to root cause & resolve problems and implement solutions to technical issues impacting application performance.
5. Collaborate with scrum master and the engineering leads to perform backlog/sprint management, prioritization, and PI planning.
6. Collaborate with international teams in the UK, Sweden, US, Japan, India, and Mexico.
7. Test, document, and quality assess new data solutions, to ensure they are fit for release.
8. Research and Development aspirations to explore, actively support, and drive the consolidation of technology stack as well as work on new technology initiatives that best fit for purpose.
9. Know when to take initiative, speak up, and are prepared to do so.
10. Have a “can do” approach to technical issues. Dig for the right technical answer that fits the need. Finding solutions to technical problems that may arise with understanding the technical issue and using all resources to solve that issue.
11. Estimation, implementation, and delivery of features and functional enhancements within the platform that can support the improvement in value, revenue, profitability, and user satisfaction.
Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.
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