Location: Charlotte, NC
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description: Job Title: Data Engineer / Data Platform Engineer (Python, PySpark)Location: Remote / Hybrid (TBD; non-NYC preferred based on team guidance)
Assignment Type: Contingent Resource
About the RoleWe are seeking a highly skilled Data Engineer to support the modernization of Financial Crimes Technology, moving from legacy vendor platforms toward scalable, cloud-native, in-house solutions. In this role, you will design and build data pipelines, enhance data quality, and enable analytics and downstream applications across critical financial crimes domains including AML, investigations, sanctions, fraud, and KYC.
You will consult on complex, large-scale engineering initiatives, analyze multifaceted technical challenges, and collaborate strategically with cross-functional teams. This role requires strong technical depth in data engineering, an understanding of regulated environments, and the ability to drive outcomes in a fast-moving environment.
ResponsibilitiesData Engineering & Platform Development- Design, build, and maintain scalable batch and/or streaming data pipelines for financial crimes use cases.
- Develop and optimize data transformation workflows using Python, PySpark, and advanced SQL.
- Apply expert knowledge of Apache Spark architecture (executors, partitions, shuffles, joins, caching) to improve processing performance.
- Support ingestion pipelines from multiple systems (transactional platforms, case management tools, reference data repositories, and more).
- Implement data quality controls, reconciliation processes, and audit-ready validations to ensure integrity and reliability.
- Contribute to modernization initiatives, including migration planning and redesign from legacy tooling to in-house frameworks.
Collaboration & Delivery- Work closely with engineering, analytics, risk, and compliance partners to translate business needs into data models, mappings, and curated datasets.
- Produce clear documentation for pipelines, logic flows, operational processes, and runbooks.
- Participate in Agile ceremonies and support sprint planning, execution, and delivery (Jira).
Required Qualifications- 5+ years of experience in Data Engineering, ETL development, or data platform engineering.
- Strong hands-on proficiency in:
- Python
- PySpark / Apache Spark
- Advanced SQL
- Experience working with large-scale datasets and performance tuning.
- Strong understanding of key data concepts:
- Data modeling
- Data governance
- Metadata and lineage
- Experience operating in regulated environments with strong process, control, and audit requirements.
- Excellent communication skills with the ability to partner across engineering and business teams.
Preferred Qualifications- Experience running PySpark workloads on Google Cloud Platform (Google Cloud Platform):
- Dataproc
- BigQuery
- Google Cloud Storage (GCS)
- Background with cloud-native data platforms, data lakehouses, or warehouses (Databricks, Snowflake, BigQuery).
- Exposure to:
- Data governance and security (encryption, data masking, PII handling)
- CI/CD workflows (Git, pipelines, automation, release management)
- Orchestration tools (Airflow or similar)
- Streaming technologies (Kafka)
- Prior experience supporting Financial Crimes programs (AML, sanctions, fraud, KYC).
Domain Expertise (Highly Valued)- Direct experience supporting:
- Anti-Money Laundering (AML)
- Transaction monitoring
- Investigations
- Sanctions screening
- Fraud programs
- Strong familiarity with regulatory expectations and documentation standards associated with risk and compliance functions.
Additional Required Qualifications- 5+ years of Software Engineering experience, or equivalent via work experience, training, military service, or education.
- Work Location: Charlotte, NC.
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