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FalconSmartIT

Data Engineer

Pay: Not specified

Posted: 1 week ago

Location: Pittsburgh, PA (Onsite)

Last Updated: 1 week ago

Hours: Full-Time

Expires: 9/27/2026

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What they do

A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.

$113,315 / year median in Pennsylvania

+12% projected growth

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Job Description

Data Engineer FalconSmartIT Pittsburgh, PA Job Details 19 hours ago Qualifications Data integrity assurance Data model design Version control Commercial use (data warehousing systems) Data Integration (Data management) Cloud data warehouses Data modeling projects Data validation techniques 5 years Spark Git Schema design Snowflake SQL Reducing cloud infrastructure costs ETL process automation Spark implementation Data integrity process (data warehousing) AWS Glue Airflow Azure Data Factory Data Security (Data management) Query execution time improvement Continuous integration Scalability Kafka DevOps automation Senior level Query management Communication skills

Full Job Description Job Title:

Data Engineer Location:

Pittsburgh, PA (Onsite) Job Type C2

C Job Description:

We are looking for a Data Engineer with 5+ years of experience and strong hands-on expertise in Snowflake, SQL, Python, and ETL/ELT. The candidate will be responsible for building scalable data pipelines, data warehouse solutions, and reliable data platforms. Design, develop, and maintain scalable ETL/ELT data pipelines. Develop and optimize complex SQL queries and Snowflake workloads Build data warehouse solutions and data models using Snowflake. Integrate data from multiple sources and implement data quality and validation processes. Optimize Snowflake performance and cloud infrastructure costs. Troubleshoot production data pipeline issues and ensure data reliability. Collaborate with analysts, data scientists, and business teams to deliver data solutions. Follow best practices for code quality, testing, version control, and documentation.5+ years of experience in Data Engineering. Strong hands-on experience with Snowflake. Advanced SQL skills. Strong experience with Python and ETL/ELT. Good understanding of data warehousing and data modelling. Experience with AWS, Azure, or GCP Experience with Git and CI/CD practices. Strong problem-solving and communication skills. Experience with Airflow, dbt, Azure Data Factory, or AWS Glue Knowledge of Spark/PySpark. Experience with Snowflake Streams, Tasks, Snow pipe, Dynamic Tables, or Snowpark Exposure to Kafka, data governance, and data security Work Experience 7-10Years