Location: Charlotte, NC
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description: Data Engineer / Data Platform Engineer (Python, PySpark)Location: Remote / Hybrid (TBD; preference for non-NYC depending on team placement)
Assignment Type: Contingent Resource
About the RoleThe Financial Crimes Technology team is modernizing its data ecosystem by shifting toward internally built platforms and reducing reliance on legacy vendor solutions. As a Data Engineer, you will build scalable data pipelines, enhance data quality, and support analytics and downstream applications across financial crimes domains such as AML, sanctions, fraud, KYC, and investigations.
You will work on complex, large-scale engineering initiatives, contributing technical insight, evaluating multi-factor challenges, and partnering closely with engineering and business teams to influence strategy and delivery.
Responsibilities- Design, build, and maintain batch and/or streaming data pipelines supporting financial-crimes use cases.
- Develop performant data transformations using Python, PySpark, and Apache Spark, optimized for large-scale datasets.
- Apply deep knowledge of Spark internals (executors, partitions, shuffles, caching, joins) to improve reliability and efficiency.
- Translate business and technical requirements into scalable data models, mappings, and curated datasets.
- Integrate data from multiple systems, including transactional platforms, case-management tools, and reference data sources.
- Implement robust data-quality checks, reconciliation steps, and audit controls.
- Support modernization efforts, including migration planning, pipeline redesign, and replacement of legacy tooling.
- Produce clear documentation for pipelines, logic workflows, architecture, and operational runbooks.
- Contribute to Agile delivery workflows (e.g., Jira), supporting sprint execution and releases.
- Collaborate with cross-functional stakeholders to drive high-impact engineering solutions.
Minimum Qualifications- 5+ years of experience in data engineering, ETL development, or data-platform engineering.
- Strong hands-on development experience with:
- Python
- PySpark / Apache Spark
- Advanced SQL
- Proven success working with large-scale datasets and optimizing data-processing performance.
- Strong understanding of data-management concepts: modeling, lineage, metadata, and governance.
- Experience working in regulated or control-heavy environments with audit-ready engineering practices.
- Excellent communication skills, with the ability to work effectively with engineering and business partners.
Preferred Qualifications- Experience running PySpark workloads on Google Cloud Platform (Google Cloud Platform), including:
- Dataproc
- BigQuery
- Google Cloud Storage (GCS)
- Experience with modern big-data and cloud-native architectures.
- Knowledge of data governance, compliance, and security best practices.
- Experience with CI/CD for data workloads, Git-based workflows, and automated release pipelines.
- Experience with orchestration or streaming technologies (e.g., Airflow, Kafka).
- Familiarity with lakehouse/warehouse ecosystems (Databricks, Snowflake, BigQuery).
- Experience implementing data security measures such as encryption, access-control, masking, and PII-handling.
- Prior experience in financial-crimes domains: AML, sanctions, fraud, investigations, or KYC.
Domain Expertise (Highly Valued)- Background supporting financial-crimes or risk-management functions, including AML transaction monitoring, sanctions screening, fraud detection, or investigative workflows.
- Comfort working with regulatory expectations, documentation standards, and audit requirements.
Additional Requirements- 5+ years of software engineering experience, or an equivalent combination of work experience, education, training, or military background.
- Primary team location: Charlotte, NC
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