What you'll do:
In Eaton, making our work exciting, engaging, meaningful; ensuring safety, health, wellness; and being a model of inclusion & diversity are already embedded in who we are - it's in our values, part of our vision, and our clearly defined aspirational goals.
This exciting role is part of a our IT team in a large multi-national company. The role offers a broad variety of responsibilities including great learning opportunities.
Brief primary function of your role:
As an EDA Data Engineer, you will set the strategy and implementation of the Lakehouse for the enterprise as part of the EDA team.
You will help in Eaton's journey to a modern, cloud-native data architecture strategy.You will be responsible for designing and implementing cloud-based solutions for Eaton. creating data mesh data pipelines , custom frameworks. You will also be responsible for setting inbound and outbound cost effective integration patterns and developing strategies for data management/data products. You should be accountable for designing technical solutions for various EDA Data Mesh Business Domains.
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Your essential responsibilities include:
1.Design and implement cloud-based solutions in Azure / AWS,snowflake,Palantir.2.Implement Mesh framework and data lake to improve the performance and scalability of the Mesh architecture.3.Work closely with the development teams to ensure that the data platform is optimized for high performance and scalability.4..Deploying CICD process across Dta flow pilines and optimizating them to meet SLA.Deploying and supporting custom based matadata framework across all layers of cloud/snowflake.
Qualifications:
Bachelor's degree in STEM from accredited university with 10+ years IT Technical Experience
Skills:
- Deep knowledge of data architectures including data lakes, warehouses, marts, lake house, graph, timeseries and in-memory solutions.
- Specific experience in cloud-based data solutions such as Azure BLOB or ADLS and Synapse, AWS S3, EMR and Redshift, Databricks, Snowflake, etc.
- Demonstrated experience with implementing solutions to monitor and improve data availability across multiple domains.
- Communication: The ability to clearly and effectively communicate complex data and analytics concepts,to non-technical stakeholders is essential for a Data Engineer.Leadership and Problem-solving: A Senior Data Engineer must be able to lead cross-functional teams and guide them through the data Engineer solution processes.Collaboration and Adaptability: A Data Engineer must be able to work collaboratively with other teams and departments to ensure that data and analytics architecture aligns with overall business goals.Strategic thinking: A Data Engineer must be able to think strategically and anticipate future data mesh technology needs.Analytical skills: A Data Engineer must be able to analyze large sets of data, identify patterns and insights, and use that information to inform decision making.