Senior BI Engineer: Data Integration & Analytics

HCSC Group; Chicago, Northern (IL, KY); Hybrid; USD 71,000 - 150,000; Full time

Job summary

Health Care Service Corporation seeks a Sr BI Engineer to design and develop data integrations delivering Enterprise BI Data Marts and semantic layers. This role uses Teradata, Hadoop, and Azure cloud to build end-to-end pipelines for DAS analytics.

You will partner with stakeholders to craft data products, support a universal semantic model, and apply DevOps practices and scheduling tools in a fast-paced BI environment.

Qualifications

• Bachelor’s degree with 2 years of experience OR Masters Degree or 6 years of equivalent experience in data integration.
• Experience with SQL
• Experience with data analytics tools and solutions
• Knowledge of BI Architecture and technologies
• Experience with data architecture teams to develop universal semantic model
• Knowledge of Hadoop stack (HDFS, Hive, HQL, Spark, Scala, PySpark)
• Knowledge of Teradata and Azure Cloud Analytics Services Synapse, ADLS, ADF, etc.
• Knowledge of DevOps/ CI tools and enterprise scheduling tools (Control-M, Zena)
• Strong communication, analytical, and multi-tasking abilities

Responsibilities

• Design and develop end-to-end data integration pipelines
• Deliver Enterprise BI Data Marts and BI semantic layers
• Collaborate with business stakeholders to design data products enabling insights
• Work with Hadoop/Teradata/Azure cloud stacks in a DAS environment

Skills

SQL

BI architecture

stakeholder collaboration

DevOps

Analytics tools

Hadoop

Spark

Python

Azure Cloud

Education

Bachelor’s degree

Master’s degree

Tools

Teradata

Hadoop

Spark

PySpark/Python

Teradata BTEQ

Azure Synapse

ADLS/ADF

Control-M

Job description

Health Care Service Corporation seeks a Sr BI Engineer to design and develop data integrations delivering Enterprise BI Data Marts and semantic layers. This role uses Teradata, Hadoop, and Azure cloud to build end-to-end pipelines for DAS analytics.

You will partner with stakeholders to craft data products, support a universal semantic model, and apply DevOps practices and scheduling tools in a fast-paced BI environment.