Data Engineer / Senior Data Engineer
ArcadiaSalary not specified
Full Time
Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
IoT, RFIDIndustries
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
Data Pipelines
IoT Data
RFID
Time-Series Data
Cloud Infrastructure
Machine Learning Workflows
Data Versioning
Data Labeling
Data Augmentation
Feature Extraction
Data APIs
Edge Computing
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.
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