Data Engineer: Build Scalable Pipelines & Analytics

MultiPlan; McLean (VA); On-site; USD 100,000 - 105,000; Full time

Job summary

MultiPlan is seeking a Data Engineer to help build and maintain scalable data infrastructure for reporting, analytics, and predictive modeling. You will partner with business users and engineering teams to translate data needs into effective solutions.

The role emphasizes data quality, governance, security, and reliability, with exposure to PHI in a HIPAA-compliant environment. High risk/privileged role responsibilities are noted.

Qualifications

• High school diploma or equivalent and four (4) years of related experience with OOP, SQL, data modeling, and data processing systems.
• Experience with Python and PySpark for advanced analytics.
• Experience with SQL, Spark, and Azure Data Factory (ADF).
• Experience triaging data issues and collaborating with business users to resolve problems.
• Experience with data governance, data quality, and data security in production.
• Ability to build and manage data pipelines and integrate analytics into business processes.

Responsibilities

• Design, build, and maintain scalable data pipelines, data warehouses, databases, and data models for reporting and analytics.
• Partner with business users and engineering teams to translate data needs into technical solutions.
• Develop and optimize queries and transformations to produce reliable data models.
• Improve performance, scalability, and quality of data solutions as data grows.
• Analyze data pipelines to identify trends, anomalies, and opportunities to boost reliability.

Skills

OOP

SQL

Data modeling

Python

PySpark

Azure Data Factory

Data governance

Communication

Problem solving

Education

Bachelor's degree in CS/IT or related field

Tools

Databricks

SSIS

Hive

Impala

Spark

Job description

MultiPlan is seeking a Data Engineer to help build and maintain scalable data infrastructure for reporting, analytics, and predictive modeling. You will partner with business users and engineering teams to translate data needs into effective solutions.

The role emphasizes data quality, governance, security, and reliability, with exposure to PHI in a HIPAA-compliant environment. High risk/privileged role responsibilities are noted.