Data Engineering Leader: Scale Real-Time Pipelines

CareFirst BlueCross BlueShield

Baltimore (MD)

On-site

USD 136,720 - 253,787

Full time

14 days+
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Job summary

CareFirst BlueCross BlueShield in Baltimore seeks a Manager of Data Engineering to lead data platforms and drive scalable data solutions across the organization. You will guide the team to deliver robust data pipelines for batch and streaming data, ensuring data quality and lineage while partnering with analytics and product teams.

The role emphasizes agile collaboration, leadership, and hands-on expertise with Snowflake, Azure Data Factory, and CI/CD practices to advance the enterprise data

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or related field (or 4 additional years of relevant experience).
  • 5 years related professional experience with at least 1 year supervisory or leadership experience.
  • Data engineering best practices: data quality, lineage, master data management.

Responsibilities

  • Lead design of scalable data pipelines for batch and real-time data ingestion and delivery.
  • Oversee data delivery services supporting operational processes, analytical models and ML applications.
  • Foster data culture and collaborate with data scientists, analytics and product teams in agile environments.

Skills

Data pipeline design
Streaming/batch processing
Snowflake
Azure Data Factory
Informatica IICS
SQL
Python
Java
Agile
Communication

Education

Bachelor's degree in CS/IT/Engineering

Tools

Azure DevOps
CI/CD pipelines

Job description

CareFirst BlueCross BlueShield in Baltimore seeks a Manager of Data Engineering to lead data platforms and drive scalable data solutions across the organization. You will guide the team to deliver robust data pipelines for batch and streaming data, ensuring data quality and lineage while partnering with analytics and product teams.

The role emphasizes agile collaboration, leadership, and hands-on expertise with Snowflake, Azure Data Factory, and CI/CD practices to advance the enterprise data

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