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Remote mid-level data engineer at strong brand with broad cloud/dataplatform requirements increases competition.
Core data engineering and cloud skills are highly transferable across industries.
Explicit 5–7 years plus specific Databricks/Snowflake/cloud/Terraform requirements make shortlisting stringent.
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Design, develop, and maintain scalable data pipelines, SDKs, APIs, and microservices supporting enterprise-wide data and analytics.
Ensure data quality, reliability, and implement data governance and platform observability best practices.
Collaborate cross-functionally with product managers, data scientists, and engineers; mentor junior engineers and participate in code reviews.
5-7 years of software development experience with strong skills in distributed systems, cloud-native architectures, and data platforms.
Proficiency in Python, SQL; hands-on experience with cloud platforms (AWS, Azure, or GCP) and data tools like Databricks, Snowflake, Apache Spark, Airflow.
Strong understanding of Lakehouse architecture, Data Mesh principles, data governance, and API-first service delivery at scale.
Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation; work experience required: 5-7 years.
Experienced in building and scaling complex data solutions in cloud environments utilizing modern data engineering frameworks and governance.
Strong operational focus evident from delivering API-first services, managing cloud infrastructure programmatically, and ensuring observability and data quality.
Able to lead and mentor others while collaborating in multidisciplinary teams involving product and data science functions.