Lead BigData Engineer

Please find details for this position below: Client: Banking/Financial Industry Title: Lead BigData Engineer / Lead BigData Architect / Lead BigData Platform Engineer / Big Data Platform Engineer - 4 Openings Location: Charlotte, NC – Hybrid Roles Duration: 12+ Month (s) Extend or Convert based on performances Job Details - 3 Openings: Required Qualifications: • 5+ years of Software Engineering experience • Financial Crimes Technology team is evolving toward more in-house build capabilities and reducing dependency on legacy vendor/tooling approaches. • This role will support data engineering and platform development for financial crimes use cases (AML, investigations, sanctions, fraud, KYC) by building scalable pipelines, improving data quality, and enabling analytics/reporting and downstream applications. Key Responsibilities: • Build and maintain batch and/or streaming data pipelines supporting financial crimes initiatives. • Develop data transformations using Python + PySpark and optimize performance for large datasets. • Apply strong understanding of Apache Spark architecture (executors, partitions, shuffles, joins, caching) to improve performance • Partner with business and technical stakeholders to translate requirements into data models, mappings, and curated datasets. • Support ingestion from multiple sources (transactional systems, case management, reference data, etc.). • Implement data quality checks, reconciliation, and controls to ensure auditability and reliability. • Contribute to modernization efforts (legacy → in-house build) including migration planning and redesign. • Create documentation for pipelines, logic, and operational runbooks. • Work within Agile delivery (Jira), supporting sprint execution and delivery timelines. Required Skills: • 5+ years of experience in data engineering / ETL / data platform development • Strong hands-on development in: • Python • PySpark / Apache Spark • Advanced SQL • Experience working with large-scale data sets and performance tuning. • Strong understanding of data concepts: data modeling, lineage, metadata, governance • Experience supporting regulated environments with emphasis on controls and audit readiness • Strong communication skills (ability to work with both engineering + business partners) Preferred Skills (Nice to Have): • Experience running PySpark workloads on Google Cloud Platform (GCP) • Dataproc, BigQuery, Google Cloud Storage (GCS), etc. • Experience with cloud native Big Data platforms • Knowledge of data governance, security, and compliance practices • Experience with CI/CD pipelines for data engineering workloads • Orchestration: Airflow (or similar scheduling tools) • Streaming: Kafka • Lakehouse/Warehouse: Databricks / Snowflake / BigQuery • CI/CD + DevOps: Git, pipelines, automation, release management • Data governance/security: encryption, access controls, data masking, PII handling • Prior Financial Crimes domain: AML / sanctions / fraud / investigations / KYC Domain Experience (Highly Valued): • Experience supporting AML, Transaction Monitoring, Investigations, Sanctions screening, Fraud, or similar risk/compliance functions. • Familiarity with regulatory expectations and strong documentation discipline. Job Details - Big Data Platform Engineer - 1 Openings Required Qualifications: • 4+ years of Software Engineering • Big Data Platform (Source, Conform, Curate) • Big Data developer (Spark, Scala, Python, Autosys, Git, etc.) • Tools Used (Spark, Python, Scala, Linux Shell, Autosys, etc.) • Home Grown Tool (Flow Master, Edit Upload, etc.) - if prior WF • Interfaces (Linux Command Line, Editors like PyCharm, Dremio, etc.) • Soft Skills (Data processing experience, Big Data experience, Data Controls experience, working in JIRA Agile) • Accountability (Lead and own work streams end to end) • Fin Crime (Domain expertise with preparing data for use cases like Transaction Monitoring, Customer Risk, Investigations, etc.) EEO: Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.