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Python Data Jobs in Minnesota (NOW HIRING)

Stellar IT Solutions

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

Develop Python data components (operators, hooks, transforms), packaging and CI/CD for deployment to Composer/Dataflow. Work with Big Data ecosystems and MPP warehouses; support data ingestion ...

Stellar IT Solutions LLC

Data Engineer

Minneapolis, MN · Hybrid

$50 - $55/hr

Data Engineer Richfield, MN 55423 (Local - Hybrid 2 Days/Week) 12+ Months Contract Project ... Python for ELT/ETL, with exposure to Postgres. Skills Overview: • SQL (5+ years) • Apache ...

Dlapiper

Data Engineer

Minneapolis, MN

$119K - $143K/yr

Proficiency in SQL and Python. * Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS). * Data warehousing experience (Azure Synapse ...

Varsity Tutors

Python Tutor

Edina, MN · Remote

$18 - $40/hr

Deep knowledge of Python syntax, data types, control flow, functions, object-oriented programming, file handling, modules and packages, list comprehensions, error handling, and popular libraries ...

Dellfor Technologies

Python Developer

Minneapolis, MN

$60K/yr

... data structures, computer networking and operating systems Development expertise in REST/SOAP/JSON API Development expertise in message bus technologies such as RabbitMQ, ActiveMQ; Apache Kafka ...

THOMSON REUTERS

Staff Software Engineer

Eagan, MN · On-site

You will be developing and implementing solutions using Python, Snowflake, AWS cloud infrastructure, and modern data engineering practices, while leading and mentoring a team of talented engineers.

RELX

Data Scientist

Minneapolis, MN · On-site

Responsibilities : • Build and deploy machine learning models using R, Python, SAS, and SQL. • ... Big Data technologies • Strong communication skills and ability to work cross-functionally ...

System One

Data Scientist

Minneapolis, MN · On-site

Write scalable, production-grade Python code to wrap models into microservices and expose them via RESTful APIs for real-time inference. * Build and maintain automated data preprocessing, feature ...

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All JobsPython Data JobsPython Data Jobs in Minnesota

Python Data information

What is the salary for Python data analytics?

The salary for Python data analysts typically ranges from $60,000 to $100,000 annually, depending on experience, location, and industry. Professionals with strong skills in data manipulation, visualization, and tools like Pandas and SQL tend to earn higher salaries.

What Python jobs are in demand?

Python data-related jobs in demand include data analyst, data scientist, machine learning engineer, and backend developer. These roles often require proficiency in libraries like Pandas, NumPy, and frameworks such as TensorFlow, with employers seeking strong programming skills and experience with data analysis or AI projects.

What are some common challenges faced by Python Data professionals when working with large datasets?

Python Data professionals often encounter challenges such as optimizing code to handle large volumes of data efficiently and managing memory usage to prevent slowdowns or crashes. Working with big datasets may require leveraging tools like pandas, NumPy, or Dask, and sometimes integrating with distributed computing systems such as Apache Spark. Additionally, ensuring data quality and managing data pipelines for consistent and accurate results can be demanding. Collaborating closely with data engineers, analysts, and other stakeholders is common to ensure smooth data flow and analysis.

What is a Python Data professional?

A Python Data professional is someone who uses the Python programming language to analyze, process, and interpret data. They work with large datasets, perform data cleaning and transformation, and apply statistical or machine learning techniques to extract insights. These professionals often work in roles such as data analyst, data scientist, or data engineer, and use Python libraries like Pandas, NumPy, and scikit-learn to accomplish their tasks.

Will AI replace Python devs?

Python developers are unlikely to be fully replaced by AI, as their role involves designing, coding, and maintaining complex software systems that require human judgment and creativity. AI tools can assist with tasks like code generation and debugging, but human oversight remains essential for quality and innovation. Staying updated with new frameworks and machine learning techniques can help Python developers remain valuable in the evolving tech landscape.

What is the difference between Python Data vs Data Analyst?

AspectPython DataData Analyst
Required SkillsPython programming, data manipulation, scriptingExcel, SQL, data visualization
CertificationsPython certifications, data science coursesData analysis certifications, Excel certifications
Work EnvironmentData science teams, programming-heavy rolesBusiness intelligence, reporting teams
Industry UsageTech, finance, healthcareRetail, marketing, finance

Python Data roles focus on programming, data manipulation, and building data pipelines using Python, while Data Analysts primarily analyze data using tools like Excel and SQL to generate reports and insights. Both roles often collaborate but differ in technical depth and tools used.

What type of jobs can I get with Python?

Python is used in a variety of roles including software developer, data analyst, data scientist, machine learning engineer, and automation engineer. These jobs often require knowledge of libraries like Pandas, NumPy, and frameworks such as TensorFlow or Django, and may involve working in environments like cloud platforms or data centers.

What are the key skills and qualifications needed to thrive as a Python Data professional, and why are they important?

To thrive as a Python Data professional, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with data analysis or data science, typically supported by a relevant degree. Familiarity with technical tools such as pandas, NumPy, SQL, Jupyter Notebooks, and often cloud platforms or machine learning frameworks is important, and certifications like Microsoft or Google Data certifications can be advantageous. Strong analytical thinking, attention to detail, and effective communication help you extract insights from data and collaborate with stakeholders. These skills and qualities are essential to efficiently process, analyze, and interpret data, driving informed business decisions.
What are popular job titles related to Python Data jobs in Minnesota? For Python Data jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Python Data jobs in Minnesota look for? The top searched job categories for Python Data jobs in Minnesota are:
Python Data jobs near you
Infographic showing various Python Data job openings in Minnesota as of July 2026, with employment types broken down into 74% Full Time, 4% Part Time, and 22% Contract. Highlights an 94% In-person, 2% Hybrid, and 4% Remote job distribution.
Data Engineer

Data Engineer

Stellar IT Solutions

Minneapolis, MN • On-site

$119K - $143K/yr

Other

Posted 14 days ago

Job description

Data Engineer

Richfield, MN 55423 (Local - Hybrid 2 Days/Week)

12+ Months Contract

Project Description:
You will be part of the Myads reporting team responsible for building the measurement, reporting, and insights platform that powers Ads and the broader Retail Media Network. In this role, you will design, develop, and maintain scalable, reliable, and high-performance data solutions that enable advertisers, merchants, and internal teams to measure campaign performance and business impact.
As a Developer, you will build and enhance data pipelines, APIs, and cloud-based services on Google Cloud Platform (Google Cloud Platform) while contributing to the architecture and implementation of measurement platforms. You will collaborate closely with Product Management, Ads Engineering, Analytics, Data Science, and other cross-functional teams to deliver high-quality solutions that meet business needs and support growth objectives. You will participate in the full software development lifecycle, including design, implementation, testing, deployment, and ongoing optimization of data and measurement systems. This role is hybrid, which means you will work some days on site at the client's location and some days virtually from home.
Position Summary/Job Description:
Hire an experienced Data Engineer to design, build, and maintain scalable batch/streaming data pipelines on Google Cloud. The role requires deep SQL expertise, production grade orchestration with Apache Airflow (Cloud Composer), and strong Python for ELT/ETL, with exposure to Postgres.
Skills Overview:
SQL (5+ years)
Apache Airflow (Cloud Composer) (3+ years)
Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, GCS, Composer) (3+ years)
Python (5+ years)
Big Data (warehousing/processing concepts, performance)(5+ years)
Postgres (3+)
Experience
Design, develop, and operate reliable data pipelines and DAGs using Apache Airflow/Cloud Composer for batch and near real time workflows.
Build ELT/ETL on Google Cloud Platform services (e.g., BigQuery, Dataflow, Pub/Sub, Cloud Storage; Composer for orchestration); enforce coding, testing, and observability standards.
Write expert level SQL for modeling, complex transformations, windowing functions, and performance tuning; own query efficiency and cost optimization.
Develop Python data components (operators, hooks, transforms), packaging and CI/CD for deployment to Composer/Dataflow.
Work with Big Data ecosystems and MPP warehouses; support data ingestion, schema evolution, and partitioning/clustering strategies.
Integrate Postgres sources/targets
Partner with product, analytics, and platform teams; uphold security, compliance, data quality (DQ checks, SLAs), and documentation standards.
What are some preferred/nice to have skills the manager is looking for?
Who has worked in ads domain.
Should be able to talk to stakeholders and understand the problem and solve it efficiently
Preventing data quality issues before they impact users.
Prioritizing projects and handling multiple requests.

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