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Polars Data Jobs (NOW HIRING)

Habitat Energy

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Pandas, NumPy, Polars, Pydantic). 'Nice to have' skills and experience: * 2+ years of orchestrating machine learning workflows. * Experience with OSS data warehousing tooling and management. * Cloud ...

Maxonic, Inc.

Data Scientist

Santa Clara, CA · On-site

Experience with data analysis and visualization tools (e.g., Pandas/Polars, NumPy, Matplotlib, Seaborn). * Knowledge of machine learning algorithms and techniques. * Familiarity with deep learning ...

Cmu

Data Scientist

Arlington, VA

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... polars, MATLAB, etc.) * Innovative and inquisitive with ability to imagine novel analytical ...

Habitat Energy

Data Engineer

Austin, TX · Hybrid

$113K - $136K/yr

Pandas, NumPy, Polars, Pydantic). 'Nice to have' skills and experience: * 2+ years of orchestrating machine learning workflows. * Experience with OSS data warehousing tooling and management. * Cloud ...

Cmu

Data Scientist

Pittsburgh, PA · On-site

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... polars, MATLAB, etc.) * Innovative and inquisitive with ability to imagine novel analytical ...

Tailored Talent

Data Platform Engineer

San Francisco, CA

$134K - $162K/yr

You know how every investment team says, "data is everything". At this firm, that's not a talking ... Python, SQL, Trino, Apache Iceberg, Polars, Spark, Dagster, and Ray all make appearances depending ...

Apogee Integration LLC

Data Scientist

Chantilly, VA · On-site

Python, R, SQL) and machine learning toolkits (e.g. pytorch, numpy, polars, scikit-learn, tensorflow, pandas) * Proficiency using mathematical, statistical, or other data-driven analysis

Cmu

Associate Data Scientist

Pittsburgh, PA · On-site

$57K - $57K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... polars, MATLAB, etc.) * Innovative and inquisitive with ability to imagine novel analytical ...

vetegrity

Data Scientist 3

Annapolis Junction, MD · On-site

... Polars - Experience with process automation for reporting and maintaining Python automation ... unstructured data - Familiarity with customer-specific tools, data flows (e.g., XKS/DX), and ...

Kforce Technology Staffing

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

Would ideally have knowledge of Python data libraries such as Pandas, DuckDb, Polars, etc. (extra points for ML libraries) * Must demonstrate proficiency in SQL, knowledge of other database systems ...

Kforce Technology Staffing

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

Would ideally have knowledge of Python data libraries such as Pandas, DuckDb, Polars, etc. (extra points for ML libraries) * Must demonstrate proficiency in SQL, knowledge of other database systems ...

Cmu

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... polars, MATLAB, etc.) * Innovative and inquisitive with ability to imagine novel analytical ...

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All JobsPolars Data Jobs

Polars Data information

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$46K

$165K

$243.5K

How much do polars data jobs pay per year?

As of Jul 7, 2026, the average yearly pay for polars data in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Polars Data vs Data Analyst?

AspectPolars DataData Analyst
Required SkillsData manipulation, programming in Python/R, familiarity with data processing librariesData interpretation, reporting, visualization skills, basic programming
Work EnvironmentData processing, scripting, working with large datasetsBusiness analysis, presenting insights, collaborating with teams
Industry UsageData engineering, data science, analytics projectsBusiness intelligence, reporting, decision support

Polars Data focuses on efficient data processing and manipulation using programming tools, often in data engineering or data science contexts. Data Analysts primarily interpret data, create reports, and support business decisions. While both roles work with data, Polars Data is more technical and programming-oriented, whereas Data Analysts focus on analysis and communication of insights.

What are some common challenges faced by professionals working with Polars Data, and how can they be addressed?

Professionals working with Polars Data often encounter challenges such as adapting to its unique API, optimizing data processing workflows for performance, and integrating Polars with other data tools. Since Polars is relatively new compared to libraries like pandas, there may be limited community support or documentation for complex use cases. To overcome these challenges, it's helpful to actively engage with the Polars community, regularly review official documentation, and experiment with different optimization strategies. Collaborating with team members familiar with similar data processing frameworks can also accelerate the learning curve.

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

To thrive as a Polars Data Engineer, you need strong skills in data engineering, Python programming, and a solid understanding of the Polars library for efficient data processing. Familiarity with data pipeline tools, cloud platforms, and proficiency in using Polars for large-scale, high-performance data manipulation is typical, alongside knowledge of version control systems like Git. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with teams and translating data needs into actionable solutions. These skills ensure you can design robust, scalable data workflows and deliver timely insights for data-driven decision-making.

What are Polars Data professionals?

Polars Data professionals are specialists who work with Polars, a fast DataFrame library designed for data manipulation and analysis, particularly in Python and Rust. They use Polars to efficiently process large datasets, perform data cleaning, transformation, and analysis tasks. These professionals often have backgrounds in data science, analytics, or software engineering, and choose Polars for its speed and scalability compared to traditional libraries like pandas. Their work is valuable in fields that require rapid data processing, such as finance, research, and technology.
More about Polars Data jobs
What cities are hiring for Polars Data jobs? Cities with the most Polars Data job openings:
What states have the most Polars Data jobs? States with the most job openings for Polars Data jobs include:
What job categories do people searching Polars Data jobs look for? The top searched job categories for Polars Data jobs are:
Polars Data jobs near you
Infographic showing various Polars Data job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Engineer

Habitat Energy

Austin, TX • On-site

$113K - $136K/yr

Full-time

Posted 12 days ago

Job description

Data Engineer
Habitat Energy is a fast growing technology company focussed on the physical and financial optimisation of energy storage and renewable generation assets globally through complex models and trading. By maximising the returns from these assets we aim to drive investment in renewable energy and accelerate the transition to a low carbon world. Our rapidly growing team of 130+ people in Austin, TX, Oxford, UK, and Melbourne, Australia brings together exceptionally talented and passionate people in the domains of energy trading, data science, software engineering and renewable energy management.
We have a vacancy for a Data Engineer to join our Austin based team.
Your responsibilities will include:
  • Supporting Data Engineering Infrastructure:
    • Contribute to the design, development, implementation and continuous improvement of our data engineering tools, workflows, processes, and platforms. This includes enhancing the architectural foundations and integrating new data management technologies.
  • Writing Well-Structured Code:
    • Develop clean, maintainable, well-documented code that adheres to best practices. Support best coding practices within Habitat's software, machine-learning, and data science teams.
  • Enhance data engineering knowledge:
    • Improve expertise within the software team and ensure their ability to support and collaborate on the data infrastructure infrastructure.
  • Data Quality Management:
    • Continuously enhance data quality across multiple dimensions such as accuracy, availability, performance, and accessibility to ensure a clear understanding of data within the company.
  • Providing backup/escalation to the tech-on-call team.
  • Communicating effectively across Software and Data Science teams.

Requirements
Preferred skills and experience:
  • 3+ years of Python experience.
  • 3+ years of working in technical teams, building data pipelines, delivering productionised code, building/maintaining live applications, developing tooling and improving backtesting frameworks.
  • Experience in applying relational database design.
  • Proficiency with Orchestration and IaC in AWS (e.g. Terraform, Kubernetes, RabbitMQ, Airflow, Prefect), Git, containerisation (Docker), database management (e.g. Postgres, Alembic).
  • Fluent in Python and its wider numerical ecosystem (e.g. Pandas, NumPy, Polars, Pydantic).

'Nice to have' skills and experience:
  • 2+ years of orchestrating machine learning workflows.
  • Experience with OSS data warehousing tooling and management.
  • Cloud infrastructure experience.
  • Experience with monitoring frameworks (e.g. Prometheus).
  • Experience archiving data to Parquet on S3 and creating tools for API/Grafana queries.
  • Experience centralising diverse datasets for analytics, visualisation and machine learning.
  • Familiarity with time-series forecasting and/or optimisation.
  • Experience with data visualisation and dashboards (e.g. Grafana, Superset).
  • Familiarity with machine learning and associated techniques (feature engineering, boosting methods, LightGBM).

Ultimately we are looking for someone who is a great fit for our company so we encourage you to apply even if you may not meet every requirement in this posting. We value diversity and our environment is supportive, challenging and focused on the consistent delivery of high quality, meaningful work.
In return, we'll give you a competitive salary, flexible working arrangements and a lot of personal development opportunities. We operate a hybrid working model with at least 2 days in our office in Austin.
When you apply for a job with us, we process some of your personal information. You can find out more about how we process your information on our company website: https://habitat.energy/privacy-policy/.
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