Sr Data Engineering Architect – Fraud Domain-5

REALIGN LLC; Cleveland (OH); On-site; USD 120,000 - 180,000; Full time

Job summary

REALIGN LLC in Cleveland, OH is seeking a Sr Data Engineering Architect – Fraud Domain to define and implement enterprise data architecture, data models, and governance standards for fraud and risk analytics.

You will design scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions, partnering with Fraud, Risk, Compliance, and Business teams to deliver AML, KYC, and regulatory reporting.

Qualifications

• 10+ years in Data Engineering, Data Warehousing, Analytics, or Data Management.
• 3+ years as a Data Architect designing enterprise-scale data solutions.
• Strong BFSI, Payments, FinTech, or Fraud/Risk domain experience, including fraud detection, AML, KYC, transaction monitoring, and risk analytics.
• Expertise in Data Architecture, Data Modeling, Data Lake/Lakehouse, Data Warehouse, ETL/ELT, Data Governance, and Metadata Management.
• Hands-on experience with SQL, Python, Spark/PySpark, Databricks, Kafka, Airflow, Snowflake, and modern cloud platforms.
• Knowledge of real-time streaming, event-driven architectures, MDM, Data Mesh, and ML/AI-enabled data platforms.
• Strong leadership, stakeholder management, communication, and solution design skills.

Responsibilities

• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives.

Skills

Leadership

Communication

Stakeholder management

Solution design

Data architecture

Tools

SQL

Python

Spark/PySpark

Databricks

Kafka

Airflow

Snowflake

Cloud platforms

Job description

Job Description

Must Have Technical/Functional Skills:

• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives.

Qualifications & Skills:

• 10+ years of experience in Data Engineering, Data Warehousing, Analytics, or Data Management.
• 3+ years of experience as a Data Architect designing enterprise-scale data solutions.
• Strong BFSI, Payments, FinTech, or Fraud/Risk domain experience, including fraud detection, AML, KYC, transaction monitoring, and risk analytics.
• Expertise in Data Architecture, Data Modeling, Data Lake/Lakehouse, Data Warehouse, ETL/ELT, Data Governance, and Metadata Management.
• Hands-on experience with SQL, Python, Spark/PySpark, Databricks, Kafka, Airflow, Snowflake, and modern cloud platforms.
• Knowledge of real-time streaming, event-driven architectures, MDM, Data Mesh, and ML/AI-enabled data platforms.
• Strong leadership, stakeholder management, communication, and solution design skills.
• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives.

Required Skills

Job Type: Full Time

Job Category: IT

Job Description

Job Title: Sr Data Engineering Architect – Fraud Domain

Location : Cleveland, OH (Onsite)
Fulltime

Job Description

Skill: Sr Data Engineering Architect – Fraud Domain

Must Have Technical/Functional Skills:

• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives.

Qualifications & Skills:

• 10+ years of experience in Data Engineering, Data Warehousing, Analytics, or Data Management.
• 3+ years of experience as a Data Architect designing enterprise-scale data solutions.
• Strong BFSI, Payments, FinTech, or Fraud/Risk domain experience, including fraud detection, AML, KYC, transaction monitoring, and risk analytics.
• Expertise in Data Architecture, Data Modeling, Data Lake/Lakehouse, Data Warehouse, ETL/ELT, Data Governance, and Metadata Management.
• Hands-on experience with SQL, Python, Spark/PySpark, Databricks, Kafka, Airflow, Snowflake, and modern cloud platforms.
• Knowledge of real-time streaming, event-driven architectures, MDM, Data Mesh, and ML/AI-enabled data platforms.
• Strong leadership, stakeholder management, communication, and solution design skills.

Roles & Responsibilities:

• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives.

Required Skills