Data Engineer / Architect (Pittsburgh, PA, 15231) | 05/13/26

Job Description Role:

Data Engineer /

Architect Location:

Pittsburgh, PA (Hybrid)

Duration:

Long Term Job Description:

Overview We are seeking an experienced Data Engineer to join our AI & Digital Team. This individual will design, build, and optimize data pipelines and infrastructure, enabling advanced analytics, process automation, and data-driven decision-making. The Data Engineer will work closely with data scientists, and IT teams to ensure data reliability and actionable insights across the data lifecycle. Key Responsibilities Develop/maintain scalable and reliable data pipelines for industrial data (like real-time streaming, time series, IoT, sensors, MES, ERP systems data)

Integrate data from different sources (databases, clouds or on-premises) and Engineer workflows for efficient ETL/ELT processing and data validation.

Collaborate with architects, data engineers, data scientists, analysts, and business stakeholders to define and deliver solutions.

Build and maintain data infrastructure in compliance with data governance and security best practices Requirements Bachelor's degree in computer science or related fields with 3-5 years' experience as a Data Engineer.

Strong experience in building, maintaining, and optimizing ETL/ELT Cloud-agnostics data pipelines using Python, Pandas, PySpark and orchestrating workflows like Apache Airflow and Kedro framework.

Advanced

SQL/ KQL

query development and optimization across Oracle, MSSQL, and MySQL databases (hosted on-premises or via PaaS offerings).

Strong understanding of cloud‑agnostic data engineering patterns, including batch vs. streaming ingestion, schema evolution, data partitioning, and cost‑optimized storage design.

Experience working with cloud object storage across providers (e.g., ADLS, S3, GCS) and designing reliable, scalable data lake or Lakehouse solutions.

Developing and consuming RESTful API (Fast API )s for data services and integration.

Proficiency in Linux shell scripting for automation.

Experience with DevOps practices, including CI/CD for data pipelines and use of tools such as Git, Docker and deployment.

Strong troubleshooting, process automation, and root-cause analysis skills

Preferred Skills:

Role Responsibility Area Preferred Tools & Skills Data Ingestion Pipeline Python, PySpark, Airflow, Kedro, Linux shell scripting API Development Flask, Fast API, RESTful design Data Storage & Querying SQL (Oracle, MSSQL, MySQL), KQL Cloud Integration Multi-cloud platforms (OCI, Azure, GCP); cross-cloud data sharing/integration using portable Spark platforms (e.g., Databricks) Platform Databricks, C3.AI Real-Time Data Streaming Kafka, Azure Event Hub, EMQX Collaboration Wiki, Azure DevOps Boards, MS Office 365