Senior Data Engineer – Remote Data Pipelines

Thrivent Financial; Minneapolis, Northern (MN, KY); Hybrid; USD 126,000 - 154,000; Full time

Benefits offered by this job

Bonuses

Medical insurance

Dental and vision insurance

401k

Pension

Paid time off

Job summary

Thrivent Financial seeks a Senior Engineer (e-MG) to advance data engineering initiatives. Based in Minneapolis with option to telecommute from anywhere in the United States, you will design and implement data pipelines, work with Hadoop/Spark/Kafka stacks, and partner with stakeholders to ensure scalable, reliable software.

The role requires 5+ years in data engineering, strong Python/Scala skills, and experience with Snowflake/Databricks and data lake architectures.

Qualifications

• Bachelor’s degree in Applied Computer Science, MIS, CS or related field with 5+ years data engineering experience.
• 5+ years in data engineering with big data tech and data integration.
• Experience with Hadoop, Spark, Kafka, Hive and Snowflake.
• Proven ability to design and implement data pipelines and data lake solutions.

Responsibilities

• Design solutions and drive outcomes for customers.
• Develop core software for the product delivering stable, scalable results.
• Collaborate with stakeholders to design data quality frameworks.
• Define data ingestion patterns with enterprise source systems; support CI/CD pipelines.
• Mentor juniors, provide technical guidance, and participate in product planning.

Skills

Hadoop

Spark

Kafka

Python

Scala

Education

Bachelor's degree in Computer Science or related field

Tools

Hive

Oracle

SQL Server

DB2

Snowflake

Databricks

Hadoop

Hive

IICS

Informatica PowerCenter

Zena

Job description

Thrivent Financial seeks a Senior Engineer (e-MG) to advance data engineering initiatives. Based in Minneapolis with option to telecommute from anywhere in the United States, you will design and implement data pipelines, work with Hadoop/Spark/Kafka stacks, and partner with stakeholders to ensure scalable, reliable software.

The role requires 5+ years in data engineering, strong Python/Scala skills, and experience with Snowflake/Databricks and data lake architectures.