Job Description
Job Description:
Build data ingestion systems that connect to APIs, SaaS platforms, customer databases, files, and event streams.
Design and develop Apache Spark pipelines that clean, normalize, validate, and enrich customer data.
Create canonical data models, metric-ready datasets, and trusted business definitions.
Build data quality, lineage, reconciliation, and observability capabilities into the platform.
Partner with AI, product, and platform engineering teams to power analytics, benchmarks, and AI-driven experiences.
Required Skills
Strong SQL, data modeling, API integration, and pipeline engineering skills.
Experience with Apache Spark and modern data platforms such as Microsoft Fabric, Databricks, Snowflake, Synapse, or similar technologies.
Strong understanding of data quality, schema evolution, lineage, reconciliation, observability, and production reliability.
High ownership, strong engineering judgment, and the ability to operate in ambiguous environments.
Qualifications
4-9 years of experience in data engineering, backend engineering, platform engineering, or distributed data systems.
Strong Computer Science, Data Engineering, Engineering, Mathematics, or STEM background; master's degree preferred.
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