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Remote role at a strong global brand, mid-level generalist title, and broad cloud-data requirements increase candidate competition.
Core data engineering skills are transferable, but lakehouse, data-mesh, and supply-chain context increase domain specificity.
Explicit 5–7 years plus mandatory Databricks, Snowflake, cloud, Terraform, and data governance skills raise strictness.
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Design, develop, and maintain scalable data solutions and pipelines with a focus on data quality and reliability.
Build SDKs, APIs, and microservices to support enterprise-wide data and analytics requirements.
Collaborate cross-functionally and mentor junior engineers while implementing best practices in software development, data governance, and platform observability.
5-7 years of experience in software development with strong skills in distributed systems and cloud-native architectures.
Strong programming skills in Python and SQL.
Hands-on experience with cloud platforms (AWS, Azure, or GCP) and tools like Databricks, Snowflake, Apache Spark, Apache Airflow.
Experience with infrastructure-as-code tools such as Terraform or AWS CloudFormation.
Experienced software engineer comfortable operating in fast-paced, collaborative environments delivering scalable data platforms.
Proficient with modern data architectures including Lakehouse and Data Mesh, and frameworks supporting data governance and observability.
Demonstrated ability to lead by mentoring junior engineers and driving API-first service solutions at scale.