Lead Data Engineer (Banking)

Job Description

Job Description

ITTConnect is seeking a Lead Data Engineer for a direct-hire full time position with a client that is a large financial institution.

Position is hybrid in Miami.

The Lead Data Engineer turns business and domain needs into secure, observable, reusable, and documented pipelines. The role combines hands-on technical leadership, portfolio delivery, consultant coordination, engineering standards, and stakeholder engagement in a regulated bank.

Key Responsibilities:

Portfolio & Delivery Leadership

• Own integrated delivery for 4-6 concurrent projects, balancing priorities, dependencies, capacity, risks, and production commitments, working under a scaled agile framework.
  
• Turn transformation needs into technical scope, milestones, acceptance criteria, and measurable outcomes.
  
• Provide portfolio visibility through dashboards, risk logs, dependency tracking, and escalation.
  
• Ensure releases meet change, security, testing, documentation, and production-readiness requirements.

Team & Consultant Coordination

• Direct an 8-12 person consultant team through work allocation, onboarding, delivery follow-up, and quality review.
  
• Set an accountable rhythm with backlog refinement, design and code reviews, stand-ups, demos, and retrospectives.
  
• Build capability through reusable patterns, playbooks, pairing, coaching, and knowledge transfer.
  
• Partner with vendor and bank leaders to manage capacity, capability, performance, continuity, and key-person risks.

On-Premises Platform Execution

• Guide solutions using NiFi for ingestion, Airflow for orchestration, dbt for transformation and testing, and SQL for processing and validation.
  
• Improve pipeline stability through modular design, automated tests, version control, disciplined deployment, observability, and incident follow-up.
  
• Prioritize technical debt by business criticality, operational risk, migration value, and delivery impact.

Cloud Transition & Re-Engineering

• Follow the AWS and Databricks operating model in line with architecture, security, governance, networking, and compliance standards.
  
• Lead cloud-native pipeline delivery and phased re-engineering of on-premises pipelines.
  
• Redesign and remodeling instead of lifting and shifting when it improves scale, reliability, cost transparency, reuse, lineage, or supportability.
  
• Define migration waves, readiness, parallel runs, reconciliation, cutover, rollback, and decommissioning.
  

Stakeholder & Domain Partnership

• Align delivery with business and data owners, stewards, architects, security, infrastructure, risk, compliance, and operations.
  
• Lead cross-domain requirements and design discussions, resolving ambiguity and clarifying trade-offs.
  
• Explain decisions, delivery health, risks, and business impact to technical and executive audiences.
  

• 15+ years of experience in IT.
  
• 8+ years in data engineering, platform delivery, analytics engineering, or a related field
  
• 3+ years in technical or delivery leadership.
  

• Experience coordinating parallel projects and distributed or consulting teams in complex enterprises.
  

• Strong SQL expertise and practical experience with NiFi, Airflow, dbt, or comparable tools.
  

• Experience building production pipelines with automated tests, quality controls, monitoring, lineage, documentation, and support.
  

• Working knowledge of AWS and Databricks architecture, lakehouse patterns, security, deployment, and migration.
  

• Experience in regulated financial services or another control-intensive environment.
  

• Strong English communication, planning, problem-solving, and stakeholder management;
  

• Fluency in Portuguese or Spanish is a plus.
  

Preferred Qualifications

• Experience with Unity Catalog, Delta Lake, Databricks Workflows, CI/CD, infrastructure as code, and cloud observability.
  
• Knowledge of AWS data-platform services, including S3, IAM, KMS, CloudWatch, and private networking.
  
• Experience with catalogs, metadata, lineage, data quality, and DataOps or DataSecOps.
  
• Familiarity with dimensional modeling, data vault, medallion/lakehouse, streaming, and data products.
  
• Relevant AWS, Databricks, data engineering, or agile delivery certifications.