Jobs · Information Technology

Sr. Data Engineer, Data Platform

Mirion Technologies · United States · 1 wk ago
RemoteRemoteInformation TechnologyFull-time

Responsibilities

  • Architect and design enterprise-scale data platforms and pipeline solutions using Spark, Azure Databricks, and related technologies.
  • Build and optimize data models and dimensional schemas for complex analytics and AI/ML use-cases.
  • Lead technical design reviews and mentor junior data engineers on best practices and architectural patterns.
  • Establish data quality, governance, and metadata management frameworks across the platform.
  • Collaborate with stakeholders to define data requirements and translate them into technical solutions.
  • Drive optimization initiatives for data pipeline performance, cost, and reliability.
  • Participate in hiring and team building for the data engineering function.
  • Contribute to architectural decisions and long-term platform strategy.
  • Troubleshoot complex data pipeline failures and implement robust monitoring and alerting solutions.

Requirements

  • 5+ years experience in data engineering, analytics engineering, or related field.
  • Expert-level SQL and experience with modern data warehouses (Snowflake, BigQuery, Redshift, etc.).
  • Deep experience designing and maintaining large-scale data pipelines using Spark, Airflow, or similar orchestration tools.
  • Strong proficiency in Python or Scala for complex data processing.
  • Advanced understanding of data modeling, dimensional design, data warehousing concepts.
  • Experience with cloud platforms (AWS, GCP, or Azure) at scale.
  • Proven ability to mentor and guide junior engineers.

Qualifications

  • Experience architecting data platforms from the ground up.
  • Experience with Databricks, Delta Lake, and lakehouse architectures.
  • Expertise in real-time data streaming and event-driven architectures (Kafka, Kinesis).
  • Knowledge of data governance, data lineage, and metadata management systems.
  • Experience with ML infrastructure and feature stores.
  • Background in regulatory-heavy industries or complex compliance requirements.
  • Experience with infrastructure-as-code and DataOps practices.

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