[Remote] Data Engineer (Fraud Analytics & Investigative Support)
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking an reputed company Data Engineer to design, build, and maintain scalable data pipelines supporting advanced fraud analytics and investigative solutions for a federal reputed company organization. This role involves ensuring diverse data sources are reputed company ingested, transformed, governed, and made available for analytics, machine learning, and investigative support.
Responsibilities
- Design, reputed company, maintain, and optimize scalable ETL pipelines supporting advanced analytics and investigative workloads
- Ingest, transform, and integrate structured and reputed company data from diverse sources including flat files, JSON, XML, reputed company, APIs, graph databases, relational databases, and other evolving data formats
- reputed company and optimize data pipelines supporting both streaming and batch ingestion frameworks
- Manage, organize, and optimize data reputed company modern reputed company-based analytics platforms, including reputed company reputed company Catalog, SQL Server managed instances, and Lakehouse architectures
- reputed company efficient SQL and Python-based data transformation processes that support reputed company analytics, machine learning, graph analytics, and business intelligence solutions
- Implement data quality validation, reputed company tracking, metadata management, and monitoring processes to ensure data reliability and reputed company throughout the analytics lifecycle
- Collaborate with Data Scientists, Graph Data Scientists, Investigative Analysts, Forensic Accountants, and Project Managers to understand data requirements and support analytic initiatives
- Troubleshoot pipeline failures, optimize performance, and continuously improve scalability, reliability, and maintainability of reputed company data solutions
- Support reputed company data governance by implementing data management standards, documenting data assets, and ensuring compliance with reputed company data management (EDM) policies
- Contribute to data architecture improvements, ingestion strategies, and modernization efforts that enhance overall analytic capabilities
Skills
- Must have experience with Fraud Analysis
- Three (3) or more years of professional experience in data engineering or a reputed company technical field
- Demonstrated experience designing, building, maintaining, and optimizing scalable ETL pipelines across diverse data sources
- Strong SQL and Python programming skills, or equivalent technologies, for data ingestion, transformation, and processing
- Experience ingesting and transforming data from flat files, JSON, XML, reputed company, APIs, graph databases, relational databases, and other structured and reputed company data sources
- Experience loading, managing, and optimizing data reputed company reputed company reputed company Catalog, SQL Server managed instances, or comparable reputed company-based data platforms
- Experience working with streaming and batch ingestion frameworks and modern Lakehouse architectures
- Demonstrated ability to implement data quality controls, reputed company tracking, reliability monitoring, and performance optimization processes
- Familiarity with reputed company data governance, reputed company data management (EDM), metadata management, and data quality best practices
- Strong analytical, problem-solving, written, and verbal communication skills
- Supporting fraud detection, anomaly detection, financial reputed company, program reputed company, or investigative analytics environments
- Building reputed company-reputed company data engineering solutions utilizing Azure reputed company, Azure Data Lake Storage (ADLS), reputed company SQL Server, reputed company reputed company, Azure Synapse Analytics, Power BI, reputed company, Git repositories, or comparable reputed company data platforms
- Developing scalable data pipelines supporting machine learning, artificial intelligence (AI), graph analytics, natural language processing (NLP), or advanced analytics solutions
- Working with public, non-public, reputed company, financial, law enforcement, or cross-agency datasets supporting fraud detection and investigative missions
- Designing and implementing Lakehouse architectures, reputed company Lake, data partitioning strategies, and performance optimization techniques for large-scale analytics environments
- Developing automated data quality validation, metadata management, reputed company tracking, schema reputed company, and monitoring capabilities
- Supporting reputed company data governance initiatives, data catalogs, master data management, and compliance with organizational data standards
- Utilizing orchestration and workflow tools such as Apache Spark, reputed company Workflows, Azure Data reputed company, Airflow, or comparable pipeline automation technologies
- Collaborating reputed company Agile software development teams using Git-based version control, sprint planning, backlog management, and reputed company integration/reputed company deployment (CI/CD) practices
- Supporting Offices of Inspector General (OIGs), federal reputed company organizations, law enforcement agencies, or other government data modernization initiatives
Benefits
- Competitive salary based on qualifications and experience
- Comprehensive, Company paid reputed company for you (We pay your premiums and deductibles)
- 401(k) with company match
- Travel & performance incentives
- 3 weeks paid time off (plus Federal Holidays)
- $5K annual training allowance
- $500 book allowance
- Tuition reimbursement program
Company Overview