Staff Data Engineer at Imprint

Seattle, Washington, United States

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

IoT, RFID, Machine LearningIndustries

Requirements

Bachelor’s degree in Data Engineering, Electrical Engineering or a related field and 8 years of related experience, or equivalent combination of education and experience
8+ years of experience in data engineering working with Machine Learning pipelines
Deep understanding of data pipeline design, ETL/ELT processes, automated workflow orchestration (e.g. Apache Airflow)
Strong programming skills in Python (especially for data workflows), with experience building scalable, maintainable pipelines (e.g. Pandas, numpy)
Strong experience with structured and unstructured databases (SQL, MongoDB, DuckDB)
Strong understanding of cloud infrastructure (AWS, Azure, or GCP), especially cloud storage, compute, and ML tools (e.g., SageMaker, Vertex AI, Azure ML)
Experience with data lake/data warehouse technologies (e.g., S3 + Glue, BigQuery, Snowflake, Delta Lake)
Knowledge of machine learning model lifecycles, including training, validation, and deployment
Understanding of data versioning, feature engineering, and ML lifecycle management
Understanding of machine learning data needs, including labeling, versioning, and model-ready dataset preparation
Familiar with distributed data systems and big data tools (e.g., Spark, Kafka, Hadoop)

Responsibilities

Design data workflows to support model training, evaluation, and retraining cycles for deployment on edge devices
Work closely with ML engineers to align data formats, labeling standards, feature extraction for edge-compatible models, and feedback loops for model improvement
Architect and maintain scalable data pipelines to ingest, process, store, and access large volumes of structured and semi-structured RFID time-series data from edge networks
Develop automated systems for data versioning, labeling, augmentation, and quality assurance
Establish and maintain data APIs and interfaces to query, consume, and update datasets
Manage large datasets using distributed storage and compute frameworks (e.g., Apache Spark, Hadoop, or Dask)
Ensure data security, compliance, and consistency across the full data lifecycle
Drive improvements in data performance and reliability, especially for low-latency ML inference use cases
Implement robust ETL/ELT workflows for preparing data for cloud-based ML model training and evaluation
Collaborate and coordinate with large scale data collection projects
Monitor and optimize data pipelines for performance, reliability, and cost across edge-to-cloud infrastructure
Optimize data flow and compute for performance, cost, and latency in hybrid edge-cloud environments

Skills

Key technologies and capabilities for this role

Data EngineeringIoT Data ProcessingCloud InfrastructureData PipelinesMachine Learning WorkflowsRFIDTime-Series DataData VersioningData LabelingData AugmentationData Quality AssuranceData APIsFeature ExtractionETLScalable Storage

Questions & Answers

Common questions about this position

What experience level is required for this Staff Data Engineer role?

The role requires a Bachelor’s degree in Data Engineering, Electrical Engineering or a related field and 8 years of related experience, or equivalent combination of education and experience, along with 8+ years of experience in data engineering working with Machine Learning.

What technical skills are needed for this position?

Key skills include experience managing large datasets using distributed storage and compute frameworks such as Apache Spark, Hadoop, or Dask, architecting scalable data pipelines for RFID time-series data, and implementing ETL/ELT workflows for ML model training.

What does the team structure look like for this role?

This is a multi-functional role requiring close collaboration with ML engineers, systems engineers, cloud architects, and embedded systems teams.

Is this a remote position, or is there a location requirement?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

Imprint

Designs and manages co-branded credit card programs

About Imprint

Imprint designs and manages co-branded credit card programs for well-known American brands. By partnering with these brands, Imprint creates credit cards that attract modern consumers, aiming to enhance the value of their partners' customer relationships. The company focuses on increasing metrics such as average spending, shopping frequency, and annual sales for cardholders. Imprint's process is notably faster than traditional credit card issuers, allowing them to launch new programs in about three months instead of the typical 18 months. Additionally, Imprint prioritizes customer service, offering a premium experience to cardholders. The goal of Imprint is to provide brands with effective credit card solutions that drive customer loyalty and sales.

New York City, New YorkHeadquarters

2020Year Founded

$197.5MTotal Funding

SERIES_CCompany Stage

Fintech, Financial ServicesIndustries

51-200Employees

Benefits

Competitive compensation and equity packages

Leading configured work computers of your choice

Unlimited vacation policy

Fully covered, high-quality healthcare including fully covered dependent coverage

Additional health coverage includes access to One Medical and option to enroll in an FSA

16 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents

An understanding that successful remote work requires flexibility and an appreciation for asynchronous work

Access to industry leading technology across all of our business units — stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity

Limited edition Imprint Credit Card (no hard pull) for the first 100 team members only. Get 1.5% cash back on all purchases, plus additional perks

Risks

Increased competition from traditional issuers adopting fintech innovations.

Potential regulatory scrutiny could increase compliance costs for Imprint.

Economic downturns may reduce transaction volumes and Imprint's revenue.

Differentiation

Imprint launches co-branded credit card programs in just three months.

Imprint offers tailored rewards programs for each brand's specific needs.

Imprint provides 'white-glove treatment' customer service to all cardholders.

Upsides

Imprint raised $75M in Series C funding to fuel innovation.

Increased consumer interest in digital wallets boosts demand for Imprint's solutions.

Partnerships with traditional banks expand Imprint's co-branded card opportunities.

Land your dream remote job 3x faster with AI

Try Jobo Free