Azure Data Engineer - Pipelines, AI & Analytics

Park Place Technologies; Cleveland (OH); Hybrid; USD 90,000 - 120,000; Full time

Job summary

Park Place Technologies in Cleveland, OH is seeking a Data Engineer to collect, clean, and transform raw data into accessible information that supports data scientists and analysts.

You will build data pipelines in Azure Synapse using Spark, Python, SQL and C#, develop ML capabilities with Azure ML, and collaborate with business users to ensure data quality.

Applicants with 2+ years in Python/SQL for data engineering and a solid SDLC background are encouraged to apply.

Qualifications

• 2+ years of Python experience for data engineering.
• 2+ years of SQL experience.
• Solid understanding of the Software Development Life Cycle.
• Strong data analytics background.
• Motivated to expand knowledge in Data Engineering, Analytics and AI.

Responsibilities

• Implement pipelines to move raw data in Azure Synapse using Spark, Python, SQL and C# in line with architectural standards.
• Develop machine learning and regression analyses in Spark-Python-Pandas, OpenAI and Azure ML.
• Employ Azure DevOps and Git following SDLC best practices.
• Interpret requirements provided by Business and Data Analysts.
• Act as a liaison with Business Analysts and Testing teams to promote smooth development execution.
• Triage and troubleshoot data aberrations reported by the user community.
• Other duties as assigned.

Skills

Data analytics

SDLC

Team collaboration

Education

Bachelor’s Degree or Relevant Certifications

Tools

Python

SQL

Spark

Pandas

Azure Synapse

Azure ML

OpenAI

Git

Azure DevOps

Job description

Park Place Technologies in Cleveland, OH is seeking a Data Engineer to collect, clean, and transform raw data into accessible information that supports data scientists and analysts.

You will build data pipelines in Azure Synapse using Spark, Python, SQL and C#, develop ML capabilities with Azure ML, and collaborate with business users to ensure data quality.

Applicants with 2+ years in Python/SQL for data engineering and a solid SDLC background are encouraged to apply.