Senior Manager – Data, Application Engineering

Jobtailor

New York (NY)

On-site

USD 150,000 - 190,000

Full time

4 days ago

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Job summary

Jobtailor seeks a Lead Data and Application Engineer to drive end-to-end lifecycle of data and application projects in the healthcare analytics space. You will design cloud-native data pipelines on GCP, build scalable microservices, and lead cross-functional teams across data, application, and integration domains.

You will collaborate with product managers, architects, and client stakeholders to define requirements, prioritize enhancements, and ensure timely delivery while mentoring teams in

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Five (5) years of backend system development experience.
Three (3) years of experience with Google Cloud Platform (GCP) for designing and deploying cloud-native data solutions.
Three (3) years of experience with Apache Beam and Kafka for distributed and streaming data processing.
Three (3) years of experience developing APIs and microservices using FastAPI and Flask.
Three (3) years of experience with Python and Shell scripting for automation and data processing.
Two (2) years of experience with Kubernetes for container orchestration and deployment.
Two (2) years of experience with Apache Airflow and DAGs for workflow orchestration.
Ability to work 40 hours per week, 9:00am–5:00pm.
Must cite job title and code EXL90 when applying.

Responsibilities

Lead the end-to-end lifecycle of data and application engineering projects, including requirements gathering, design, development, deployment, and production support.
Architect and implement cloud-based data pipelines using distributed and streaming technologies for healthcare analytics.
Oversee scalable applications and APIs for ingestion, processing, and delivery of healthcare data using microservices architecture.
Manage cross-functional teams across data, application, and integration domains.
Collaborate with product managers, architects, and client stakeholders to define technical requirements and prioritize solution enhancements.
Provide technical leadership on Google Cloud Platform, Apache Beam, Airflow, Kubernetes, FastAPI, Flask, Redis, and Shell scripting.
Ensure project alignment, technical compliance, and timely delivery.
Work at various and unanticipated worksites throughout the United States.

Skills

GCP

Apache Beam

FastAPI

Flask

Kubernetes

Redis

Python

Shell scripting

Kafka

Apache Airflow

API Development

Education

Bachelor's degree in Computer Science/IT/Engineering

Tools

Google Cloud Platform

Apache Beam

Apache Airflow

Kubernetes

FastAPI

Flask

Redis

Kafka

Job description

Lead the end-to-end lifecycle of data and application engineering projects, including requirements gathering, design, development, deployment, and production support
Architect and implement cloud-based data pipelines using distributed and streaming technologies for healthcare analytics
Oversee scalable applications and APIs for ingestion, processing, and delivery of healthcare data using microservices architecture
Manage cross-functional teams across data, application, and integration domains
Collaborate with product managers, architects, and client stakeholders to define technical requirements and prioritize solution enhancements
Provide technical leadership on Google Cloud Platform, Apache Beam, Airflow, Kubernetes, FastAPI, Flask, Redis, and Shell scripting
Ensure project alignment, technical compliance, and timely delivery
Work at various and unanticipated worksites throughout the United States

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
Five (5) years of backend system development experience
Three (3) years of experience with Google Cloud Platform (GCP) for designing and deploying cloud-native data solutions
Three (3) years of experience with Apache Beam and Kafka for distributed and streaming data processing
Three (3) years of experience developing APIs and microservices using FastAPI and Flask
Three (3) years of experience with Python and Shell scripting for automation and data processing
Two (2) years of experience with Kubernetes for container orchestration and deployment
Two (2) years of experience with Apache Airflow and DAGs for workflow orchestration
Ability to work 40 hours per week, 9:00am–5:00pm
Must cite job title and code EXL90 when applying

Core Competencies

Demonstrates expertise in architecting and implementing cloud-based data solutions, with a strong focus on Google Cloud Platform and distributed data processing technologies. Proven ability to lead cross-functional teams and manage the end-to-end lifecycle of data and application engineering projects in the healthcare domain.

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