Real-Time Data Platform Engineer (Lakehouse & Streaming)

Everseen

Herndon (AR)

On-site

USD 120,000 - 180,000

Full time

7 days ago

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Job summary

Everseen is seeking a data platform engineer to own the pipelines and data platform behind our vision AI products. You will turn six petabytes of daily video and event data into actionable data for models and analytics.

You will work with a modern tech stack including Snowflake, Databricks, Python, SQL, and streaming systems like Kafka and Spark. This role focuses on building scalable, cost-aware data solutions in a fast-moving, collaborative environment.

Qualifications

3-5 years building data platforms or pipelines in production.
Deep understanding of data modeling, performance tuning and cost management.
Strong hands-on experience with Snowflake and Databricks.
Proven experience building streaming and real time data apps with Kafka/Spark/Flink.
Proficient in Python and SQL for ETL and automation.
Familiarity with cloud platforms, Docker, Kubernetes and CI/CD for data workloads.
Excellent communication and collaborative skills.

Responsibilities

Design and build data pipelines and platform powering model training and real-time inference.
Own data modeling activities to align structures with business needs.
Collaborate on cloud-based lakehouse solutions with product and engineering teams.
Build and run streaming apps moving data from stores to the platform with low latency.
Model, store and serve large data volumes on Snowflake and Databricks.
Ensure data quality, lineage, observability and cost-aware operations.
Drive cross-functional alignment and contribute to shared tooling and standards.
Evaluate new data/streaming tools and adopt those that fit needs.