Data Engineer designing and building scalable ETL/ELT pipelines for enterprise-grade analytics solutions. Collaborating with product teams to deliver high-quality, secure, and discoverable data.
Responsibilities
Join a team of builders shaping enterprise-grade data products and platforms that power analytics, customer experiences, and operational insights at scale.
Design, build, and operate reliable batch and streaming data pipelines.
Architect and implement scalable ETL/ELT pipelines and services using modern data platforms and best practices.
Build streaming and micro-batch data flows, including schema evolution, late/out-of-order events handling, and exactly-once delivery semantics.
Model data for analytics and ML using layered “bronze/silver/gold” patterns.
Embed observability (logging, metrics, tracing), data quality checks, and cost/performance optimization into everything you ship.
Automate testing and deployments with CI/CD.
Collaborate with domain SMEs and data product owners to define requirements, acceptance criteria, and success metrics.
Operate what you build: participate in on-call/incident response rotations and drive RCA and preventative engineering.
Requirements
Bachelor's in Computer Science, Engineering, or equivalent experience will be considered in lieu of degree
5+ years building data pipelines at scale with a modern data stack
Strong proficiency in Python and SQL, plus performance tuning of both
Hands-on experience with distributed compute (e.g., Apache Spark) and lakehouse/warehouse paradigms
Data modeling for analytics (dimensional/medallion), data contracts, and schema management
CI/CD (Git-based workflows) and infrastructure-as-code (e.g., Terraform) in a cloud environment
Practical knowledge of data security, privacy, and access control concepts.
Benefits
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions.
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