Senior Data Engineer - Hybrid, Azure Data Pipelines & ML

Park Place Technologies; Cleveland (OH); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Park Place Technologies in Cleveland, OH is seeking a Senior Data Engineer to design and convert complex data into actionable insights for data scientists and analysts. You will guide junior engineers and implement robust data governance to ensure high-quality analytics.

You will build pipelines in Azure Synapse using Spark, Python, SQL, and C#, and contribute to ML initiatives with OpenAI and Azure ML. Collaboration with analysts and adherence to SDLC are essential.

Qualifications

• 4+ years of Python development for data engineering.
• 4+ years of SQL for data engineering.
• Experience designing and implementing complex data pipelines.
• Solid understanding of data warehouse and delta lake concepts.
• Strong data analytics background.
• Knowledge of the Software Development Life Cycle (SDLC).

Responsibilities

• Build pipelines to move and transform data in Azure Synapse using Spark, Python, SQL and C# per architectural standards.
• Develop machine learning and regression analysis skills with Spark, Python (Pandas), OpenAI, and Azure ML.
• Mentor junior Data Engineers and provide guidance to the team.
• Collaborate with Data Analysts and Business Analysts to clarify requirements.
• Provide peer review to ensure coding standards are followed.
• Demonstrate mastery of the Software Development Life Cycle.

Skills

Python

SQL

Data pipelines

Data warehouse

Delta lake

Data analytics

SDLC

Education

Bachelor’s Degree or Certifications

Job description

Park Place Technologies in Cleveland, OH is seeking a Senior Data Engineer to design and convert complex data into actionable insights for data scientists and analysts. You will guide junior engineers and implement robust data governance to ensure high-quality analytics.

You will build pipelines in Azure Synapse using Spark, Python, SQL, and C#, and contribute to ML initiatives with OpenAI and Azure ML. Collaboration with analysts and adherence to SDLC are essential.