Senior Data Platform Engineer

CRAFTSMAN+

Senior Data Platform Engineer role at Craft involves building and optimizing data pipelines. Join a leading supplier risk intelligence company headquartered in the US.

Posted 7/10/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering with a strong focus on building and optimizing data pipelines, applying machine learning techniques, and leveraging modern tools for efficient data processing. Proficient in Python and familiar with a variety of technologies to ensure the reliability and scalability of data systems.

Highest-signal resume keywords

Data Pipeline DevelopmentPython ProgrammingETL/ELT TechniquesMachine Learning ApplicationInfrastructure-as-Code

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringPythonETLBatch ProcessingStreamingData LakesSQLMachine LearningSoftware Development Life CycleData Modeling

Soft Skills

Problem SolvingEffective CommunicationCuriosityInitiativeIndependence

Tools & Technologies

PySparkPandasElasticSearchAirflowDockerDatabricksAWSCircleCIGitHubTerraform

Industry Keywords

Data EngineeringData StrategyObservabilityFault ToleranceScalability

Tech Stack

Tools & technologies

AirflowAWSDockerDynamoDBElasticSearchETLPandasPostgresPySparkPythonSDLCSQLTerraform

About the role

Key responsibilities & impact

Build and optimize data pipelines (batch and streaming).
Extracting, analyzing and modeling rich and diverse datasets of structured and unstructured data.
Design software that is easily testable and maintainable.
Support in setting data strategies and our vision.
Keep track of emerging technologies and trends in the Data Engineering world, incorporating modern tooling and best practices at Craft.
Work on extendable data processing systems that allows to add and scale pipelines.
Apply machine learning techniques such as anomaly detection, clustering, regression classification, and summarization to extract value from our data sets.
Leverage AI-powered development tools (e.g. Cursor) to accelerate development, refactoring, and code generation.

Requirements

What you’ll need

4+ years of experience in Data Engineering.
4+ years of experience with Python.
Experience in developing, maintaining, and ensuring the reliability, scalability, fault tolerance, and observability of data pipelines in a production environment.
Have fundamental knowledge of data engineering techniques: ETL/ELT, batch and streaming, DWH, Data Lakes, distributed processing.
Strong knowledge of SDLC and solid software engineering practices.
Familiar with infrastructure-as-code approach.
Demonstrated curiosity through asking questions, digging into new technologies, and always trying to grow.
Strong problem solving and the ability to communicate ideas effectively.
Self-starter, independent, likes to take initiative.
Familiarity with at least some of the technologies in our current tech stack: Python, PySpark, Pandas, SQL (PostgreSQL), ElasticSearch, Airflow, Docker
Databricks, AWS (S3, Batch, Athena, RDS, DynamoDB, Glue, ECS, Amazon Neptune)
CircleCI, GitHub, Terraform
Knowledge surrounding AI-assisted coding and experience with Cursor, Co-Pilot, or Codex

Benefits

Comp & perks

Competitive salary starting at $170,000 USD/ year.
Equity at a well-funded, fast-growing startup
Unlimited vacation time so you can take what you need, when you need it
99% covered health + dental + vision insurance for employees and dependents
401K through Empower with options to invest how you want it