Airflow Architect Big Data Systems

Job Summary

Need an experienced Airflow Architect to design, architect, and lead enterprise-scale data orchestration solutions for modern big data platforms. The ideal candidate will have deep expertise in Apache Airflow, Big Data technologies, cloud-native architectures, and data engineering best practices to build scalable, reliable, and high-performance data pipelines.

Key Responsibilities

Architect and implement large-scale data orchestration frameworks using Apache Airflow.

Design, develop, and optimize ETL/ELT pipelines for batch and near real-time processing.

Build scalable workflows integrating Hadoop, Spark, Kafka, Databricks, data lakes, and data warehouses.

Define Airflow deployment strategies, DAG standards, security, monitoring, and governance.

Implement workflow scheduling, dependency management, error handling, retries, alerting, and SLA monitoring.

Lead cloud-based data platform implementations on AWS

Optimize pipeline performance, scalability, reliability, and cost efficiency.

Establish CI/CD processes and DevOps practices for Airflow environments.

Collaborate with business stakeholders, data engineers, architects, and platform teams to translate requirements into technical solutions.

Mentor engineering teams on Airflow architecture, data orchestration patterns, and best practices.

Required Skills

Airflow & Data Engineering

Expert knowledge of Apache Airflow DAG design, scheduling, operators, sensors, and executors.

Strong experience in workflow orchestration, metadata management, and pipeline monitoring.

Hands-on expertise in ETL/ELT development and data pipeline automation.

Big Data Technologies

Apache Spark / PySpark

Hadoop ecosystem

Apache Kafka

Data Warehousing concepts

Data Lakes and Lakehouse architectures

NoSQL databases

Programming

Python (advanced)

SQL (advanced)

Shell scripting

Core Java (preferred)

Cloud Platforms

AWS (EMR, Glue, S3, Redshift)

Preferred Qualifications

10+ years of experience in data engineering and big data platforms.

3+ years of architecture experience designing enterprise data solutions.

Experience with Kubernetes, Docker, and cloud-native deployments.

Knowledge of Data Mesh, Data Fabric, and Modern Data Platforms.

Experience leading architecture reviews and technology strategy discussions.

Success Metrics

Pipeline reliability and SLA adherence

Workflow performance optimization

Reduced operational incidents

Improved data quality and observability

Scalable and reusable orchestration frameworks