Senior Data Engineer: Azure Data Pipelines & Mentorship

There's Only One Place; Michigan; On-site; USD 120,000 - 180,000; Full time

Job summary

There’s Only One Place is seeking a Senior Data Engineer to design and implement data pipelines, mentor junior engineers, and collaborate with analysts to translate requirements into scalable data solutions.

The role emphasizes data accessibility, governance, and leveraging technologies like Spark, Python, SQL, and cloud platforms to optimize performance and enable data-driven decisions.

Qualifications

• 4+ years of Python development for data engineering (Spark, Pandas).
• 4+ years of SQL experience for data engineering tasks.
• Design and implement complex data pipelines with data quality.
• Strong knowledge of data warehouse and Delta Lake concepts.
• Solid data analytics background.
• Familiar with the Software Development Life Cycle.

Responsibilities

• Implement pipelines to move raw data in Azure Synapse using Spark, Python, SQL and C# in line with established architectural standards related to Data Warehouse and Data Lakehouse modeling standards.
• Developing machine learning and regression analysis skills in spark-python-pandas, openai and Azure ML.
• Mentoring other members of the Data Engineering team, specifically those in a junior role
• Work closely with Data Analysts and Business Analysts to clarify their requirements and provide clear guidance on the execution process.
• Providing peer review support to work produced by others, confirming use of relevant coding standards.
• Demonstrate mastery of the Software Development Life Cycle.

Skills

Python

SQL

Data pipelines

Data warehouse

Delta lake

SDLC

Education

Bachelor’s Degree

Certifications

Tools

Azure Synapse

Spark

Azure ML

Job description

There’s Only One Place is seeking a Senior Data Engineer to design and implement data pipelines, mentor junior engineers, and collaborate with analysts to translate requirements into scalable data solutions.

The role emphasizes data accessibility, governance, and leveraging technologies like Spark, Python, SQL, and cloud platforms to optimize performance and enable data-driven decisions.