Key Responsibilities and Accountabilities - Develops, executes, troubleshoots, and improves Python-based ETL/ELT pipelines for ingestion, staging, transformation, mapping, validation, and output generation.
- Uses SQL to query, transform, validate, reconcile, and load warehouse data; optimizes queries and resolves database issues.
- Integrates data from core banking, lending, deposit, servicing, third-party, spreadsheet, CSV, flat-file, and other approved sources.
- Maintains source-to-target mappings, schemas, data models, field definitions, relationships, historical structures, lineage, and downstream dependencies.
- Resolves missing or malformed files, incorrect dates, duplicates, nulls, schema or data-type changes, mapping errors, and unexpected balances.
- Executes recurring and ad hoc data processes in the required order and delivers approved staging, intermediate, and final outputs on schedule.
- Uses Git or comparable version control and follows peer review, testing, release, change-control, and rollback practices.
- Monitors production workflows using logging, alerting, retries, backfills, backups, and recovery procedures.
- Performs root-cause analysis across source data, manual inputs, code, mappings, databases, interfaces, and reports.
- Maintains runbooks, data dictionaries, lineage, mappings, control documentation, and knowledge-transfer materials.
- Communicates status, exceptions, risks, dependencies, and business impact; supports cross-training and backup coverage.
Data Quality, Reconciliation and Controls - Reconciles source-system totals to staged and warehouse data, portfolio and financial reports, and CECL outputs.
- Validates completeness, accuracy, consistency, timeliness, uniqueness, reasonableness, row counts, balances, reporting dates, and expected ranges.
- Identifies, investigates, documents, escalates, and resolves processing and data-quality exceptions.
- Maintains critical data elements, mappings, definitions, ownership, source fields, lineage, and sensitive-data classifications in coordination with data owners.
- Retains audit evidence, including run logs, validation and reconciliation results, approvals, exceptions, source files, outputs, and processing documentation.
- Tests and documents changes to source systems, code, mappings, schemas, interfaces, procedures, and reporting requirements before production use.
- Supports audits, regulatory examinations, model validations, and management reviews involving data lineage, controls, reconciliations, and reporting.
Security, Governance and Operational Reliability - Protects customer information, regulated data, confidential Bank information, and production credentials in accordance with Bank requirements.
- Follows least privilege, role-based access, segregation of duties, user-access review, and approved production-access procedures.
- Promptly reports suspected data loss, unauthorized access, security events, material processing errors, and control failures.
- Complies with applicable Information Security, Data Governance, Privacy, Records Retention, Business Continuity, Change Management, Incident Response, and Acceptable Use requirements.
- Coordinates ownership, approvals, issue resolution, and evidence with business and control functions; supports continuity, recovery, and incident response.
Supervision of Personnel - No direct supervisory responsibilities unless assigned. May provide technical guidance, peer review, cross-training, and work coordination.
Travel - Limited travel may be required for business, vendor, training, or project needs.
Working Conditions Normal office environment; extensive use of computer; lifting up to 30lbs. The incumbent will be expected to be able to work Monday through Friday and work will mainly be performed at the Maitland location; occasional evening and weekend work may be required. Flexibility with work location and hours may be granted if circumstances permit.
Qualifications Summary Education - Bachelor's degree in computer science, Information Technology, Information Systems, Data Engineering, Data Analytics, Mathematics, Finance, Accounting, or a related field; or an equivalent combination of education, training, and relevant experience.
Experience - Five or more years of progressively responsible experience in data engineering, ETL/ELT, database development, analytics engineering, data warehousing, or a related discipline.
- Experience supporting production pipelines, recurring data processes, reconciliations, controlled releases, and audit-ready evidence.
- Experience investigating data-quality issues across files, transformation logic, mappings, databases, interfaces, and reports.
Knowledge & Skills: - Strong hands-on Python and SQL skills, including development, testing, troubleshooting, complex queries, transformation, reconciliation, loading, and performance optimization.
- Proficiency in ETL/ELT, data warehousing, source-to-target mapping, schema management, data modeling, lineage, historical data, and downstream dependencies.
- Knowledge of data-quality testing, version control, peer review, release management, change control, and rollback procedures.
- Knowledge of production monitoring, backfills, backup, recovery, incident response, and secure data handling.
- Strong attention to detail, root-cause analysis, problem-solving, documentation, prioritization, time management, and communication skills.
- Ability to execute controlled procedures on schedule, maintain complete audit evidence, and collaborate with technical, business, and control functions.
(Reasonable accommodations may be made to enable individuals with disabilities to perform these tasks. If you need an accommodation, please contact us at
[email protected] )
