Senior Data Analyst

SN Cloud Solutions; Chicago (IL); Hybrid; USD 110,000 - 170,000; Full time

Job summary

SN Cloud Solutions is hiring a Senior Data Analyst to support analytics and reporting through modern data platforms and reliable data pipelines in Chicago, IL. The role emphasizes Python and PySpark to process large datasets and ensure data quality.

With 10+ years of experience across data analytics and engineering, you will translate business needs into scalable data solutions, collaborate with data engineers and stakeholders, and document data flows and transformation logic.

Qualifications

• 10+ years of experience in data analytics, data engineering, or related technologies.
• Strong understanding of ETL/ELT workflows and data pipelines.
• Experience with cloud data platforms and modern data architectures.

Responsibilities

• Understand business and technical data requirements and translate them into practical data solutions.
• Partner with teams across databases, data lakes, and modern data fabric architectures.
• Develop, maintain, and troubleshoot ETL/ELT data pipelines.

Skills

Strong data analytics

10+ years of experience

Analytical and problem-solving skills

Python knowledge

Tools

Python

PySpark

Databricks

Azure Data Factory

Azure

Snowflake

Microsoft Fabric

AWS

GCP

SQL

Job description

SN Cloud Solutions is hiring a Senior Data Analyst to support analytics and reporting through modern data platforms and reliable data pipelines. This hybrid role in Chicago, IL (60619) focuses on working with large datasets, ETL/ELT workflows, and distributed processing, with a strong emphasis on Python and PySpark.

With 10+ years of experience, you will help translate business and technical needs into data solutions while collaborating across data engineering and analytics stakeholders. The role also includes troubleshooting pipelines, improving performance and scalability, and documenting data flows and transformation logic.

What you’ll do

• Understand business and technical data requirements and translate them into practical data solutions.
• Partner with teams working across databases, data lakes, and modern data fabric architectures.
• Develop, maintain, and troubleshoot ETL/ELT data pipelines.
• Work with structured and semi-structured data from multiple sources.
• Use Python and PySpark to support data processing, transformation, and analysis.
• Conduct data cleansing, transformation, validation, and data quality checks.
• Optimize data processing jobs and pipelines for performance and scalability.
• Collaborate with data engineers, analysts, and business stakeholders to deliver usable outputs.
• Support data integration and migration activities.
• Document data flows, transformation logic, and technical processes.

What you bring

• Strong understanding of data analytics and data concepts.
• 10+ years of experience in data analytics, data engineering, data integration, or related data technologies.
• Understanding of databases, data lakes, and data fabric.
• Hands‑on or strong conceptual knowledge of ETL/ELT processes and tools/packages.
• Good knowledge of Python.
• Good understanding of Apache PySpark and distributed data processing.
• Understanding of data transformation, data quality, and data integration.
• Strong SQL and database fundamentals.
• Good analytical and problem-solving skills.

Technology areas you’ll work with

• Python, PySpark (Apache PySpark)
• ETL, ELT
• SQL
• Databricks
• Azure Data Factory, Azure
• Snowflake, Microsoft Fabric
• AWS, GCP

Preferred qualifications

• Experience with cloud data platforms such as Azure, AWS, or GCP.
• Knowledge of modern data warehouse/lakehouse architectures.
• Experience with tools such as Databricks, Azure Data Factory, Snowflake, Microsoft Fabric, or similar platforms.
• Understanding of data governance and data quality concepts.
• Experience working in Agile environments.