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Polars Data Jobs (NOW HIRING)

Node.Digital

Senior Data Engineer

Washington, DC · Remote

$120K - $163K/yr

PySpark and Polars preferred. Experience developing reusable, modular code preferred. PREFERRED QUALIFICATIONS * DP-203, Microsoft Certified Azure Data Engineer Associate, or an equivalent current ...

Velocity Search Group Inc.

Sr. Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

Proficiency in Python and experience with data processing frameworks such as Apache Spark, Pandas, or Polars. * Hands-on experience with orchestration tools such as Apache Airflow * Experience with ...

Cmu

Data Scientist

Pittsburgh, PA

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 · 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 ...

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 ...

Apple

WPC Apple Card Data Scientist

Cupertino, CA · On-site

... Polars) with experience working with relational databases, including SQL, and large-scale distributed systems such as Redshift Proficient in cloud data platforms such as Snowflake and Databricks ...

Alt

Data Engineer

Atlanta, GA · On-site +1

$155K - $165K/yr

Proven experience with large-scale data processing using dataframe technologies (Pandas, Polars, PySpark, or similar) * Hands-on experience with pipeline orchestration tools (Airflow, Dagster, or ...

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 ...

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 ...

Cmu

Senior 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 ...

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Showing results 21-40

All JobsPolars Data Jobs

Polars Data information

See salary details

$46K

$165K

$243.5K

How much do polars data jobs pay per year?

As of Aug 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 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 is a Polars Data professional?

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 August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Senior Data Engineer

Node.Digital

Washington, DC • Remote

$120K - $163K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago

Job description

Senior Data Engineer

Location: Herndon, VA (Remote Work)

Must have an Public Trust Clearance

KEY RESPONSIBILITIES

      Provide authoritative expertise on data engineering methods and best practices, including code first development approaches and modern pipeline design patterns.

      Design, implement, and maintain the data architecture that supports products and end users, with all assets managed under source control.

      Design, implement, and maintain ELT and ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning, using both SDK V1 and SDK V2.

      Migrate source data identified by SBA OIG into Azure Data Lake Storage.

      Normalize entity attributes such as addresses, phone numbers, and other common fields.

      Review, maintain, and improve existing architecture and pipelines, including periodic audits addressing bottlenecks, deprecated dependencies, and architecture drift.

      Establish quality controls across all pipelines and introduce error handling, logging mechanisms, and validation checks.

      Incorporate source control across all pipelines and analytics codebases so code can evolve iteratively without destabilizing the architecture.

      Optimize ingestion, processing, and storage across a wide variety of datasets and data types, including modern columnar formats such as Parquet.

      Develop self service capabilities that let SBA OIG analysts query and export data for investigations and audits.

      Author robust standard operating procedures governing the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in the Azure environment.

      Produce detailed documentation of the data architecture, including data dictionaries, entity relationship diagrams, and pipeline process maps.

      Maintain and expand the environment with additional datasets and services on request, following a defined intake and testing process before production deployment.

      Stay current with emerging AI tooling relevant to data engineering and contribute to exploratory work evaluating automation and language model assisted capabilities.

Requirements

Education

Bachelor's degree in data engineering, computer science, data science, machine learning, mathematics, or a related field. Alternatively, five years of applied work experience in any of the same fields.

  • 5 years -Maintaining SQL databases and conducting advanced operations in SQL and T-SQL.
  • 5 years - Designing, implementing, and maintaining ELT and ETL processes in cloud based data analytics environments.
  • 3 years -Working in Azure Synapse and Azure Machine Learning with the modern data stack. Certifications preferred, DP-203 or equivalent.
  • 3 years -Manipulating data in Python. Pandas is required. PySpark and Polars preferred. Experience developing reusable, modular code preferred.

PREFERRED QUALIFICATIONS

  • DP-203, Microsoft Certified Azure Data Engineer Associate, or an equivalent current certification.
  • Implementing pipelines and infrastructure using code first approaches: Python SDK, CLI, REST APIs, or infrastructure as code tooling such as Terraform or Bicep.
  • Implementing source control and continuous integration and delivery workflows for data assets.
  • Demonstrated familiarity with AI coding assistants and large language model integration patterns.
  • PySpark or Polars at production scale.
  • Entity resolution and attribute normalization across records with inconsistent addresses, names, and identifiers.
  • Building self service analytic access for non engineering users.

Benefits

We are proud to offer competitive compensation and benefits packages to include

  • Medical 
  • Dental
  • Vision
  • Basic Life 
  • Health Saving Account
  • 401K matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training

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