Software Engineer, Backend – Python

Adelaide

. Design, build, and maintain backend services and APIs in Python for Adelaide’s measurement products .

Posted 9/15/2026full-timeRemote • United StatesMid-LevelSenior💰 $140,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining backend services and APIs using Python and FastAPI, with a strong focus on high-throughput data ingestion and system reliability. Proficient in collaborating with cross-functional teams to integrate data models and enhance system architecture.

Highest-signal resume keywords

Python Backend DevelopmentFastAPI FrameworkAWS Services (Kinesis, S3, RDS)Data Pipeline Orchestration (Airflow)Production API Testing (pytest)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonFastAPIAsyncioPostgresPydanticMypyDockerTerraformOAuth2CI/CD (GitHub Actions)

Soft Skills

CollaborationProblem-SolvingCode Review

Tools & Technologies

AWSAirflowLookerTableauQuickSight

Industry Keywords

ETLELTData EngineeringData ScienceHigh-Volume APIs

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSDockerETLPandasPostgresPythonTableauTerraform

About the role

Key responsibilities & impact

Design, build, and maintain backend services and APIs in Python for Adelaide’s measurement products
Build and maintain async Python services on FastAPI
Develop high-throughput APIs that ingest tracking data at scale
Build partner-facing services exposing segments and scoring to demand-side platforms
Collaborate with Data Engineering and Data Science to integrate models and data pipelines into production services
Contribute to Airflow-orchestrated ETL/ELT workflows
Write, test, and maintain clean code
Participate actively in code reviews
Diagnose and resolve production issues
Contribute to monitoring, alerting, and reliability improvements
Improve system architecture, performance, and developer workflows
Partner with Product and Customer Success to translate requirements into shipped features
Work with AWS services including Kinesis Firehose, S3, RDS/Postgres, Redshift, and MWAA Airflow

Requirements

What you’ll need

3–5 years of professional software engineering experience, with most of it in Python
Proven experience building and maintaining production backend services or APIs in Python
Experience with FastAPI or a comparable async framework
Solid testing with pytest and code review practices
Comfort with asyncio-based services, request batching, latency, and throughput in high-volume, low-latency APIs
Working knowledge of Pydantic or similar for request/response validation and settings management
Comfort with static typing using mypy
Working experience with AWS, including Kinesis/Firehose, S3, and RDS or similar
Experience with relational databases, especially Postgres
Comfort working with moderately large datasets
Exposure to data pipeline/orchestration tools such as Airflow
Ability to work cross-functionally with Data Engineering, Data Science, and Product
You’ll need to be in NYC a few times per year
Exposure to data pipeline or workflow tools such as Airflow, or data tooling like Pandas, Polars/PyArrow
Experience with OAuth2/JWT-based authentication flows
Familiarity with uv or another modern Python package/dependency manager
Familiarity with Ruff or similar linting/formatting tooling
Experience with structured logging and observability practices
Comfort with Docker and Docker Compose
IaC experience, ideally with Terraform; CloudFormation also a plus
Exposure to AWS Glue, EMR, or Lambda
Familiarity with ECS
Basic knowledge of data visualization or BI tools such as Looker, Tableau, or QuickSight
Exposure to CI/CD tooling such as GitHub Actions or AWS CodeBuild

Benefits

Comp & perks

Medical, dental, and vision insurance
Paid time off
Parental leave
Employee development & wellness stipend
Holiday break
Volunteer time off
Competitive salary
Performance-based quarterly bonus
Stock options
401(k) retirement plan
Remote-first environment
New York office access
Access to available WeWork spaces
Education budget to support ongoing professional growth and development
Access to a broad network of investors and advisors
Mentorship from executives with decades of experience in adtech and media
Regular internal knowledge-sharing sessions