Integration Engineer

Sonata Software•Irving, TX

9h•Remote

About The Position

We are seeking a highly skilled Senior Integration Engineer with 7-10 years of experience in data engineering, cloud technologies, and enterprise integration solutions. The ideal candidate will have strong expertise in AWS cloud services, Python, SQL, Databricks, workflow orchestration, and modern DevOps practices. This role requires the ability to independently analyze business requirements, identify gaps, develop robust data solutions, and build scalable data pipelines while collaborating with cross-functional teams.

Requirements

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
7-15 years of hands-on experience in Data Engineering, Cloud Engineering, or Integration Engineering roles.
Proven experience designing and supporting enterprise-scale data platforms and integration solutions.
Strong analytical, problem-solving, and troubleshooting skills.
Experience working in Agile development environments and collaborating with cross-functional teams.
Excellent communication and stakeholder management skills.
Cloud & Infrastructure: AWS (S3, EC2, IAM, Lambda, CloudWatch preferred), Docker, Kubernetes
Data Engineering: Python, Advanced SQL, Data Pipeline Development, ETL/ELT Processes, Databricks
Workflow Orchestration: Apache Airflow, Astronomer
Database & Migration: Database Design and Optimization, Alembic, Schema Migration Management
DevOps: CI/CD Pipelines, Git/GitHub/GitLab, Code Quality & Release Management
Testing & Automation: Python-based Test Automation, AI-assisted Testing Frameworks (Grok or equivalent AI-powered testing platforms)

Nice To Haves

PySpark and Spark Optimization
AWS Glue
Terraform or Infrastructure as Code (IaC)
Kafka or Event-Driven Architectures
Snowflake or Modern Data Warehouses
REST API Development and Integration
Monitoring Tools (Datadog, Prometheus, Grafana)
Machine Learning and AI Integration Exposure
Healthcare domain experience
Experience with Large Language Models (LLMs) and AI-enabled automation frameworks

Responsibilities

Design, develop, and maintain scalable and reliable data ingestion, transformation, and integration pipelines using Python and SQL.
Build and manage cloud-native data solutions within the AWS ecosystem, leveraging services such as S3, EC2, IAM, and other relevant services.
Develop, enhance, and maintain database migration frameworks using Alembic, ensuring seamless schema evolution with minimal downtime.
Orchestrate, monitor, and optimize complex data workflows using Apache Airflow and Astronomer.
Collaborate with product owners, data engineers, analysts, and business stakeholders to understand requirements and deliver production-grade solutions.
Lead and support migration initiatives to Databricks, improving performance, scalability, and analytics capabilities.
Create automated validation and testing frameworks using Python and AI-assisted testing tools/frameworks (e.g., Grok, AI-enabled testing platforms).
Identify process gaps, recommend improvements, and independently design solutions to enhance system reliability and efficiency.
Implement containerized applications using Docker and deploy workloads on Kubernetes to ensure scalability and high availability.
Drive CI/CD implementation, code quality standards, release management, and infrastructure automation.
Monitor system performance, troubleshoot production issues, and optimize cloud resources for cost and operational efficiency.
Ensure adherence to security, governance, and best practices for cloud and data engineering platforms.