Hybrid Data Engineer: AI-Driven Pipelines & Data Platforms

CFS; South Bend (IN); Hybrid; USD 125,000 - 140,000; Full time

Job summary

CFS in South Bend, IN (hybrid) is seeking a Data Engineer to design, build, and optimize reliable data pipelines and systems. The role blends hands-on data engineering with Python/SQL development and automation, leveraging AI tools to improve workflows across the platform.

Responsibilities include ETL/ELT design, data modeling, APIs, and data-driven solutions, with a focus on data quality, security, and performance in a fast-paced environment.

Qualifications

• 5+ years of experience in Data Engineering or related field.
• Strong Python and SQL development skills.
• Experience with data processing libraries such as Pandas and NumPy.
• Hands-on experience designing/maintaining production ETL/ELT workflows.
• Familiarity with workflow orchestration tools (Airflow, Dagster, Prefect).
• Experience with cloud data platforms (Snowflake, Databricks, BigQuery, Redshift).
• Knowledge of data modeling, transformation, validation, and quality management.
• Experience with AI-powered development tools and ML/LLM integrations.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Develop automated data collection, integration, and web scraping solutions.
• Create and manage data models, validation frameworks, and monitoring.
• Build APIs and internal apps to improve data accessibility.
• Collaborate with stakeholders to deliver data-driven solutions.
• Leverage AI and automation to enhance workflows.
• Support improvements and evolution of the data platform.
• Ensure data quality, integrity, performance, and security.

Skills

Python

SQL

Data engineering

Tools

Pandas

NumPy

Airflow

Dagster

Prefect

Snowflake

Databricks

BigQuery

Redshift

AWS

Docker

Terraform

CI/CD

pgvector

Pinecone

Weaviate

Job description

CFS in South Bend, IN (hybrid) is seeking a Data Engineer to design, build, and optimize reliable data pipelines and systems. The role blends hands-on data engineering with Python/SQL development and automation, leveraging AI tools to improve workflows across the platform.

Responsibilities include ETL/ELT design, data modeling, APIs, and data-driven solutions, with a focus on data quality, security, and performance in a fast-paced environment.