Data Engineer
VORKIS knows what employer wants- Location
- US
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 0–72,000/yr
Posted 2mo ago
Data Engineer - VORKIS knows what employer wants | Career Page
Data Engineer
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Job Openings Data Engineer
About the job Data Engineer
Salary
$0 - $72,000 per year
Location
, US
Employment option
Remote
Job type
Full time
Job Summary
Seeking a Data Engineer to design and build scalable data pipelines focused on large datasets and high-throughput data streams for a US-based FinTech client.
Skills
Must Have
Hard skills
novice in
Data Quality
beginner in
Big Data, Data Pipelines
competent in
ETL, Data Engineering, SQL, Pipeline, JAVA
Nice-to-have
Hard skills
novice in
GCP, AI, AWS, Cloud Platforms, Azure
beginner in
FinTech, Kafka, Elasticsearch, Real-Time Processing, Cloud Storage, Redis, B2B
Job Description
Additional Requirements
Strong Data Engineering experience, SQL and database knowledge, experience with ETL, batch or streaming processing, programming skills in Java or similar, pipeline design skills, and ability to explain architectural decisions.
Responsibilities
Design and build data pipelines (batch or streaming), process large volumes of data, ensure data validation, deduplication, and consistency, ingest data from files, cloud storage, or streams, prepare data for analytics, make architectural decisions.Benefits
- Work from home
About Company
Company Overview
You will be part of an international engineering team focused on developing a modern, intelligent surveillance platform for financial institutions. The system processes high-frequency market data to identify irregular behavior and ensure regulatory compliance across jurisdictions.
This role offers exposure to complex engineering challenges, financial domain knowledge, and the opportunity to shape a next-generation platform from within a collaborative and technically strong team.
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- Line
- X (Formerly Twitter)
Skills
- Data Quality
- Big Data
- Data Pipelines
- ETL
- Data Engineering
- SQL
- Pipeline
- JAVA
- GCP
- AI
- AWS
- Cloud Platforms
- Azure
- FinTech
- Kafka
- Elasticsearch
- Real-Time Processing
- Cloud Storage
- Redis
- B2B
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