Diverse Lynx
Position: Risk & Fraud Data Engineer
Location: Redmond, WA ( Onsite)
Job Description:
Experience with Risk Analysis and Fraud Detection is mandate.
Experience in data engineering, with at least 3 years working hands‑on with
PySpark ,
Azure Data Factory , and
Python
in production environments.
Strong background in designing and implementing
large‑scale data pipelines , including batch and real‑time ingestion for risk, fraud, or financial datasets.
Deep experience with
PySpark
for distributed data processing, data quality validation, data enrichment, feature engineering, and fraud‑signal extraction.
Solid expertise in
Azure Data Factory
for orchestrating complex ETL/ELT workflows across multiple data sources.
Proficiency in
Python
for data processing, automation, API integration, anomaly‑detection scripts, and model‑ready dataset preparation.
Strong SQL skills, including query optimization, performance tuning, and working with both relational and non‑relational stores such as
Cosmos DB ,
Kusto , or
ADLS .
Good understanding of
data warehousing , dimensional modeling, and data quality frameworks used in risk scoring and fraud detection systems.
Exposure to the broader
Azure ecosystem
such as Synapse, Databricks, EventHub, Service Bus, Key Vault, Functions, Monitor, Log Analytics, and other platform components used in risk and fraud architecture.
Familiarity with streaming architectures and patterns such as
event‑driven pipelines, near real‑time scoring, and anomaly monitoring .
Experience working with
high‑volume, sensitive data
while adhering to security, compliance, and privacy guidelines.
Strong analytical and problem‑solving abilities, with the ability to troubleshoot complex data pipeline issues in a risk or fraud context.
Effective communication skills to work with engineering, analytics, and fraud operations teams.
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.
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Experience with Risk Analysis and Fraud Detection is mandate.
Experience in data engineering, with at least 3 years working hands‑on with
PySpark ,
Azure Data Factory , and
Python
in production environments.
Strong background in designing and implementing
large‑scale data pipelines , including batch and real‑time ingestion for risk, fraud, or financial datasets.
Deep experience with
PySpark
for distributed data processing, data quality validation, data enrichment, feature engineering, and fraud‑signal extraction.
Solid expertise in
Azure Data Factory
for orchestrating complex ETL/ELT workflows across multiple data sources.
Proficiency in
Python
for data processing, automation, API integration, anomaly‑detection scripts, and model‑ready dataset preparation.
Strong SQL skills, including query optimization, performance tuning, and working with both relational and non‑relational stores such as
Cosmos DB ,
Kusto , or
ADLS .
Good understanding of
data warehousing , dimensional modeling, and data quality frameworks used in risk scoring and fraud detection systems.
Exposure to the broader
Azure ecosystem
such as Synapse, Databricks, EventHub, Service Bus, Key Vault, Functions, Monitor, Log Analytics, and other platform components used in risk and fraud architecture.
Familiarity with streaming architectures and patterns such as
event‑driven pipelines, near real‑time scoring, and anomaly monitoring .
Experience working with
high‑volume, sensitive data
while adhering to security, compliance, and privacy guidelines.
Strong analytical and problem‑solving abilities, with the ability to troubleshoot complex data pipeline issues in a risk or fraud context.
Effective communication skills to work with engineering, analytics, and fraud operations teams.
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.
#J-18808-Ljbffr