Data Engineer - Spark & Scala
Overview
As a Data Engineer, you'll design and build ETL pipelines that feed a data lake supporting Spark and Scala workloads. Your pipelines will power anomaly detection models and AI agents, handling a growing portfolio of network data sources. Part of the Apex Systems team in Denver, Colorado, you'll work onsite in Greenwood Village with remote flexibility. This role focuses on building robust and scalable data infrastructure to ensure data quality and availability for downstream consumers.
What You'll Do7
- 1Design and implement ETL pipelines using Spark and Scala to ingest data from diverse network sources.
- 2Build and maintain data lake tables ensuring data quality and availability for downstream analytics.
- 3Develop data transformations and anomaly detection logic to support AI models.
- 4Scale existing pipelines to handle increasing data volumes and complexity.
- 5Monitor pipeline performance and debug failures to guarantee reliability.
- 6Collaborate with data scientists to deliver data for feature engineering and model training.
- 7Document pipeline architecture and data dictionaries for cross-team use.
Requirements8
- 15+ years in data engineering or related field.
- 23+ years building ETL pipelines with Spark and Scala.
- 3Experience with data lake architectures like Delta Lake or Iceberg.
- 4Proficiency in SQL and Python for data processing.
- 5Knowledge of cloud platforms such as AWS or Azure.
- 6Familiarity with workflow orchestration tools (Airflow, Dagster).
- 7Understanding of distributed computing principles.
- 8Strong problem-solving and debugging skills in data environments.
Salary Insight
$146 - $166k per year
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