Data Engineer: Build Scalable Pipelines with AI

Armstrong World Industries; Rohrerstown (PA); On-site; USD 125,000 - 145,000; Full time

Benefits offered by this job

Medical, dental, prescription drug

401k match

Long-term disability coverage

Vacation and sick time

Job summary

Armstrong World Industries is seeking a Data Engineer in Lancaster, PA to design, build, and maintain scalable data pipelines and data lakehouse architecture. You will collaborate with data scientists and analysts to enable AI-driven insights and reliable analytics across the organization.

You should have strong SQL, Python, Databricks/Snowflake experience, and a proven track record with ETL/ELT workflows, data governance, and cloud platforms such as AWS or Azure.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred).
• 5+ years of experience as a Data Engineer or similar role.
• Strong knowledge of SQL, Python, and data lakehouse technologies.

Responsibilities

• Design and Develop Data Pipelines: Build and optimize data pipelines for batch and real-time data ingestion, transformation, and delivery.
• Data Modeling and Data Lakehouse Development: Design scalable data models for analytics and ML initiatives.
• Data Architecture and Harmonization: Build scalable data architecture across diverse data sources with data quality in mind.
• ETL/ELT Development: Develop robust ETL/ELT workflows using tools like dbt, Airflow, Databricks, Glue.
• Data Integration and Cloud Infra: Ingest data from APIs/databases; manage AWS/Azure/GCP data environments.

Skills

SQL

Python

Databricks

Snowflake

Airflow

LLMs

CI/CD

Git

ETL

Education

Bachelor's degree in Computer Science or related

Tools

Databricks

Snowflake

dbt

Airflow

Glue

Git

Job description

Armstrong World Industries is seeking a Data Engineer in Lancaster, PA to design, build, and maintain scalable data pipelines and data lakehouse architecture. You will collaborate with data scientists and analysts to enable AI-driven insights and reliable analytics across the organization.

You should have strong SQL, Python, Databricks/Snowflake experience, and a proven track record with ETL/ELT workflows, data governance, and cloud platforms such as AWS or Azure.