Lead Data Engineer

Convey Health Solutions • Fort Lauderdale, FL

2h • $125,000 - $145,000

About The Position

The Lead Data Engineer is both a technical authority and individual contributor
for delivery, and continuous improvement of healthcare data products and
platform components. With a proven track record of architecting secure,
high-throughput pipelines and directing the work of high-performing teams (4-5
engineers), they are responsible for translating business strategy into data
engineering execution. They guide the team in the adoption of tools like AWS
Glue, Iceberg, SageMaker, and feature flag frameworks while ensuring HIPAA and
HITRUST compliance. They will lead in best practices for
ingesting/cleaning/validating client data and orchestrate a streamlined
implementation process to onboard new clients and increase the efficiency of
existing ones.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field of study, or equivalent experience
• 10+ years in data engineering roles.
• Extensive experience working with large-scale data systems and cloud-based architectures (AWS).
• Python, PySpark, Scala (10+ yrs) – Directed large-scale data platform development with an emphasis on modularity and performance.
• Airflow (6+ yrs) – Defined standards for DAG design, observability, and reusability across the team.
• AWS (Glue, EMR, Lambda, Step Functions) (5+ yrs) – Oversaw hybrid orchestration strategies using serverless and EMR-based pipelines.
• Iceberg (4–5 yrs) – Led lakehouse strategy including governance, versioning, and cost optimization.
• Deep expertise in designing and optimizing data lake and lakehouse architectures at scale, including governance, schema evolution, cost efficiency, and access control.
• Leads strategy and implementation of hybrid lakehouse ecosystems leveraging technologies like Iceberg, Delta Lake, and catalog services across multiple environments (e.g., dev, staging, prod).
• Directed team of data engineers of 5–8 engineers, driving architecture decisions, enforcing engineering standards, and championing Agile delivery practices within a high-performance data engineering environment.
• Docker/Kubernetes (6–8 yr) – Oversaw Kubernetes-based orchestration for enterprise data pipelines; established Docker standards across teams and integrated container practices with compliance and DevOps strategies.
• Excellent written, verbal, and interpersonal communication skills.
• Excellent organizational skills and attention to detail.
• Excellent documentation skills.
• Team player.
• Ability to provide clear and accurate information through multiple media.
• Ability to extrapolate, from historical trends, future volumes, and staffing needs.
• Ability to manage open requests and follow up when necessary, without outside direction.
• Ability to manage time effectively with strong attention to detail.
• Ability to read and interpret documents including safety rules, operating and maintenance instructions, procedure manuals and general correspondence.
• Ability to write routine reports and correspondence.
• Ability to deal with problems involving several concrete variables in standardized situations.
• Ability to interact politely, tactfully, and firmly with a wide range of people and personalities.
• Ability to work in an environment with potential interruptions.
• Ability to manage multiple simultaneous tasks with individual timeframes and priorities.
• Ability to motivate and encourage a team of front-line employees.
• Ability to set and manage to expectations for a team.

Nice To Haves

• Prior experience with healthcare or regulated datasets strongly preferred.

Responsibilities

• Lead the creation of automated data validation frameworks to ensure client data integrity is at the level needed for our solutions
• Follow best practices and coding standards to create custom scripts to clean/map/align client data to the expected inputs for the ETL pipelines of various solutions
• Architect and lead the adoption of serverless data platforms, integrating services like AWS Glue, Lambda, DynamoDB, and Lakehouse Formation.
• Lead GitOps strategy for infrastructure and pipeline deployment, ensuring compliance, rollback safety, and peer-reviewed workflows.
• Establish best practices for feature flag toggling strategies in critical data pipelines.
• Drive internal knowledge sharing and technical writing culture, including mentoring junior staff on documentation standards.
• Thrives in collaborative team environments and takes pride in mentoring junior team members by providing guidance, support, and best practices.
• Adept at designing scalable architectural solutions while effectively communicating complex concepts to both technical and non-technical audiences. Skilled in tailoring messaging and presentation style based on audience needs to ensure clarity, alignment, and impact across stakeholders.
• Owns technical environment and tooling strategy across the data engineering organization. This role ensures standards, documentation, and collaboration practices are in place and consistently applied.

Benefits

• health and welfare benefits
• 401(K) savings with employer matching
• paid time off
• life, AD&D and disability insurances
• various ancillary benefits, such as pet insurance, virtual physical therapy, and employee assistance programs

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees