Data Engineering Lead

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.

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Position is hybrid in Miami.

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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.

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Key Responsibilities:

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Portfolio & Delivery Leadership

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

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

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

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

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

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• 15+ years of experience in IT.
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• 8+ years in data engineering, platform delivery, analytics engineering, or a related field
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• 3+ years in technical or delivery leadership.
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• Experience coordinating parallel projects and distributed or consulting teams in complex enterprises.
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• Strong SQL expertise and practical experience with NiFi, Airflow, dbt, or comparable tools.
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• Experience building production pipelines with automated tests, quality controls, monitoring, lineage, documentation, and support.
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• Working knowledge of AWS and Databricks architecture, lakehouse patterns, security, deployment, and migration.
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• Experience in regulated financial services or another control-intensive environment.
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• Strong English communication, planning, problem-solving, and stakeholder management;
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• Fluency in Portuguese or Spanish is a plus.
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Preferred Qualifications

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