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Director Data Engineering (Orlando)
Director Data Engineering (Orlando)LHH • Orlando, FL, US
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Director Data Engineering (Orlando)

Director Data Engineering (Orlando)

LHH • Orlando, FL, US
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  • [job_card.part_time]
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Director of Data Engineering

Remote Opportunity

Orlando, FL

Must be 40% Hands on Technical (Can still code with the best of them) and 60% Leadership, Strategy, Vision

Salary : $225k-$250k Base and Annual Bonus

Healthcare Benefits, Dental, Vision, 6% Match on 401k

Overview

We are seeking a highly technical and execution-driven Director of Data Engineering who can lead both our Core Data Engineering team and our B2B marketing data platform. This role requires a hands-on AWS-native expert who can architect scalable data frameworks, build high-quality data products, and elevate engineering excellence across the organization.

You will guide a team of 1015 engineers while serving as the technical backbone for our AWS-based data ecosystemspanning ingestion, orchestration, warehousing, analytics, and privacy-safe marketing activation.

The ideal candidate blends strong technical depth with the leadership maturity to influence product, marketing, privacy, governance, and C-level stakeholders. You thrive in ambiguity, make proactive decisions, and build systems that stand the test of scale, reliability, compliance, and cost efficiency.

Responsibilities

Strategic & Product Leadership

  • Own the technical vision and long-term roadmap for Core Data Engineering and the B2B marketing data platform .
  • Drive measurable improvements in data reliability, availability, quality, and time-to-insight .
  • Partner with Product to co-own platform strategy, ensuring value delivery to internal users and external enterprise clients.
  • Anticipate architectural evolution needs, including :
  • Medallion / lakehouse patterns
  • Privacy-safe audience activation
  • Clean room innovation
  • Marketing data integrations
  • Navigate cross-functional alignment with C-level leaders, providing clarity, influence, and strong narrative around technical decisions.

Team & Execution Leadership

  • Lead, mentor, and scale a high-performing engineering team with a culture grounded in :
  • Accountability
  • Autonomy
  • Excellence
  • Continuous improvement
  • Drive clarity around roles, expectations, and ownership; build mission-driven teams that deliver.
  • Establish engineering frameworks and best practices that minimize manual work and maximize reusability.
  • Partner with Data Governance, Legal, and Privacy teams to ensure compliant use of first-party data.

    • Technical Leadership & Architecture

    (Critical hiring manager priority must be AWS-native and hands-on)

  • Architect end-to-end AWS data systems, including :
  • AWS Glue (PySpark / ETL)
  • Step Functions & MWAA (Airflow) for orchestration
  • Redshift + Iceberg storage patterns
  • Lambda, API Gateway, Cognito for serverless integrations
  • Design metadata-driven, scalable frameworksnot just pipelinesincluding :
  • Dynamic ingestion frameworks
  • Reusable transformation patterns
  • Schema evolution and lineage tracking
  • Oversee integrations with marketing, adtech, social, and transactional platforms.
  • Guide deployment and operationalization of ML models (segmentation, recommendations, forecasting).
  • Ensure robust IAM practices, cost optimization, observability, and disaster recovery readiness.
  • Create engineering golden paths and standardization across the DE org.

    • Qualifications

    Required

  • 10+ years in data engineering roles, with 57+ years leading data or platform engineering teams.
  • Deep, hands-on expertise with AWS-native technologies :
  • Glue, Step Functions, MWAA (Airflow)
  • Lambda, API Gateway, Cognito
  • Redshift (including tuning), Iceberg tables, S3
  • SNS / SQS, EventBridge, Batch
  • Strong experience architecting big data, ETL, medallion / lakehouse , and distributed systems.
  • Proficiency in Python, PySpark, SQL , and API / microservices patterns.
  • Strong knowledge of IAM, cost optimization, monitoring / alerting, and CI / CD (GitHub Actions, Terraform / CloudFormation).
  • Proven experience aligning engineering with business KPIs, marketing needs, and product goals.
  • Excellent communication, influencing skills, and the ability to operate in politically complex environments.

    • Preferred

  • Experience building engineering frameworks (not just pipelines).
  • Experience supporting marketing platforms, clean rooms, or first-party data activation.
  • Experience with metadata-driven orchestration or pipeline engines.
  • ML model deployment experience (segmentation, LTV, recommendation pipelines).
  • Strong SDLC, agile leadership, and architectural documentation skills.

    • What Success Looks Like

  • A reliable, scalable, AWS-native data platform powering internal and external data products.
  • Material improvements in :
  • Time-to-insight
  • Data reliability
  • Pipeline reusability
  • Cost efficiency
  • A high-performing, growing, and diverse engineering team.
  • Clear engineering frameworks that standardize how data moves from ingestion transformation analytics activation.
  • Trusted partnerships with Product, Privacy, Data Science, and C-level stakeholders.
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