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Seasonal Backend Developer Python Jobs in Carmel, IN

Eightelevengroup

Sr. Data Scientist

Indianapolis, IN · On-site

$80 - $88/hr

Collaborate with backend engineers to integrate geospatial features into production systems ... Strong proficiency in Python for geospatial data analysis and modeling (GeoPandas, Shapely, Fiona ...

The AES Group

Microsoft Fabric Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

... backend engineering experience delivering production-grade data pipelines, integrations, and ... Strong proficiency in Python and/or PySpark for pipeline orchestration, data transformation, API ...

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Seasonal Backend Developer Python information

See Carmel, IN salary details

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How much do seasonal backend developer python jobs pay per year?

As of Sep 10, 2026, the average yearly pay for seasonal backend developer python in Carmel, IN is $148,003.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,300.00 and $167,200.00 per year, depending on experience, location, and employer.

What is a seasonal backend developer python?

Seasonal Backend Developer Python jobs are temporary positions where developers use the Python programming language to build and maintain server-side applications for a specific period, often aligned with a company’s peak business season. These roles typically involve working on APIs, databases, and backend logic to support web or mobile applications. Employers seek individuals who can quickly adapt, contribute to ongoing projects, and help handle increased workloads during busy times, such as holidays or special events. Candidates should have strong Python skills, familiarity with backend frameworks like Django or Flask, and experience working with databases and cloud platforms.

What are the key skills and qualifications needed to thrive as a seasonal backend developer python?

To excel as a Seasonal Backend Developer Python, you need strong proficiency in Python programming, backend frameworks (such as Django or Flask), and experience with databases, usually supported by a relevant degree or equivalent experience. Familiarity with version control systems like Git, cloud platforms such as AWS or Azure, and containerization tools like Docker is often required. Problem-solving, effective time management, and teamwork are vital soft skills for handling project deadlines and collaborating remotely or with cross-functional teams. These skills ensure efficient, scalable backend solutions that meet seasonal business demands and integrate seamlessly with broader systems.

What are some typical challenges faced by a seasonal backend developer python, and how can applicants prepare for them?

Seasonal Backend Developers working with Python often face tight project timelines and the need to quickly adapt to existing codebases. Since the role is temporary, ramping up effectively and collaborating with permanent team members are essential. Applicants can prepare by familiarizing themselves with common Python frameworks (such as Django or Flask), practicing reading and debugging unfamiliar code, and honing their communication skills to integrate smoothly with established workflows. Being proactive in asking questions and seeking documentation can make the transition faster and more effective.

What is the difference between Seasonal Backend Developer Python vs Backend Developer?

AspectSeasonal Backend Developer PythonBackend Developer
Required SkillsPython, Django/Flask, REST APIs, SQLPython, Django/Flask, REST APIs, SQL
Work EnvironmentTemporary, project-based, often remote or on-siteFull-time, permanent, on-site or remote
Industry UsageSeasonal projects in e-commerce, retail, or event-driven industriesContinuous development in tech, finance, healthcare

Seasonal Backend Developer Python roles focus on short-term projects requiring Python expertise, often in retail or e-commerce during peak seasons. In contrast, Backend Developers typically hold ongoing roles with broader responsibilities. Both roles require similar technical skills, but their employment duration and project scope differ.

Seasonal Backend Developer Python jobs near you

Sr. Data Scientist

Indianapolis, IN • On-site

Eightelevengroup
See more jobs at Eightelevengroupexternal

$80 - $88/hr

Other

Re-posted 6 days ago

Key responsibilities

  • Design and execute geospatial analyses to support product and business decision-making

  • Build, validate, and maintain spatial data models and pipelines

  • Create maps, dashboards, and visualizations to communicate findings to technical and non-technical stakeholders

Job description

Geospatial Data Scientist

Remote

This is a Remote role.

Compensation: $80 - $88 per hour

ABOUT THE ROLE

Our client is seeking a Geospatial Data Scientist to transform complex spatial data into actionable insights and support product and business decision-making. In this role, you will work across the full geospatial data pipeline—from data ingestion and processing to analysis, modeling, and visualization—and collaborate closely with engineering and product teams to embed spatial intelligence into our platform. You will be responsible for developing and maintaining spatial data models, applying machine learning techniques to spatial problems, and creating compelling visualizations for diverse stakeholders. The ideal candidate thrives in a fully remote, asynchronous environment and brings a solid understanding of geospatial standards, coordinate reference systems, and data quality management.

WHAT YOU'LL DO
  • Design and execute geospatial analyses to support product and business decision-making
  • Build, validate, and maintain spatial data models and pipelines
  • Query and manage geospatial datasets using PostgreSQL with PostGIS
  • Work with geospatial data formats including GeoJSON, Shapefile, GeoTIFF, WKT, and WKB
  • Develop machine learning models with spatial components (clustering, classification, interpolation, etc.)
  • Create maps, dashboards, and visualizations to communicate findings to technical and non-technical stakeholders
  • Collaborate with backend engineers to integrate geospatial features into production systems
  • Evaluate and maintain geospatial data quality, coverage, and accuracy
  • Apply GIS tools (QGIS, ArcGIS, or equivalent) for spatial analysis and visualization
  • Ensure clear communication of geospatial insights in a remote, async environment
  • Maintain familiarity with geospatial standards, coordinate reference systems, and spatial indexing
  • Contribute to spatial data infrastructure and cloud-native geospatial workflows as needed
WHAT YOU BRING
  • 3–6 years of experience in data science, GIS, or a related field
  • Strong proficiency in Python for geospatial data analysis and modeling (GeoPandas, Shapely, Fiona, Rasterio, or similar)
  • Deep experience with PostgreSQL and PostGIS for spatial querying and data management
  • Familiarity with geospatial standards and formats (GeoJSON, Shapefile, GeoTIFF, WMS/WFS, WKT, WKB, etc.)
  • Experience with GIS tools such as QGIS, ArcGIS, or equivalent
  • Solid understanding of coordinate reference systems (CRS), projections, and spatial indexing
  • Experience applying machine learning techniques to spatial problems
  • Ability to communicate findings clearly in a fully remote, async environment
  • Experience with remote sensing or satellite imagery analysis (nice to have)
  • Familiarity with cloud-native geospatial tools (PostGIS on AWS RDS, Google Earth Engine, etc.) (nice to have)
  • Exposure to spatial data infrastructure (GeoServer, MapServer, Mapbox, Deck.gl) (nice to have)
  • Experience with big geospatial data processing (Apache Sedona, H3, S2) (nice to have)
  • Knowledge of Docker and containerized data workflows (nice to have)
  • Familiarity with CI/CD and version control best practices (nice to have)
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