Airflow Developer

Data Engineer / Airflow Developer

Remote Shift Time: 11:00 AM to 9:00 PM IST Experience: 3+ Years Employment Type: Contract

Overview

We are looking for an experienced Data Engineer / Airflow Developer with strong hands-on experience in Snowflake, Apache Airflow, dbt, SQL, and Python. The candidate will be responsible for developing scalable data pipelines, orchestrating enterprise data workflows, building analytics-ready datasets, and supporting production data platforms.

Design and develop scalable ETL/ELT pipelines using Snowflake, dbt, Python, and Apache Airflow. Build and maintain Airflow DAGs for orchestration, scheduling, monitoring, and dependency management. Develop modular and reusable dbt models, macros, tests, and documentation. Build and maintain production-grade data warehouse solutions focused on performance, scalability, reliability, and maintainability. Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality datasets. Implement dimensional data modeling, including star and snowflake schemas, normalization, and denormalization. Ensure data quality, lineage, governance, and observability across data pipelines and warehouse layers. Optimize Snowflake performance and cost through query tuning, warehouse sizing, clustering, and compute/storage optimization. Integrate Snowflake with multiple data sources, including cloud storage, APIs, streaming systems, and third-party applications. Build and maintain CI/CD pipelines for automated deployment of Airflow and dbt workflows. Monitor, troubleshoot, and resolve pipeline failures, performance issues, and production incidents. Follow best practices around Git, release management, testing, and Infrastructure-as-Code (IaC). Required

3+ years of experience in Data Engineering, including at least 2 years of hands-on Snowflake experience. Strong expertise in SQL and Python for large-scale data processing and transformation. Strong hands-on experience with Apache Airflow for workflow orchestration and scheduling. Strong practical experience with dbt, including:

Experience building enterprise ETL/ELT pipelines using dbt, Airflow, Matillion, Talend, or equivalent tools. Strong understanding of data warehousing, dimensional modeling, and data architecture. Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with Git-based version control and CI/CD. Experience implementing data quality checks, governance standards, and security controls. Strong understanding of Snowflake architecture, performance tuning, query optimization, and cost optimization.

Snowflake certifications such as SnowPro Core or SnowPro Advanced. Experience with streaming and real-time ingestion technologies such as Kafka or Spark Streaming. Exposure to BI/analytics tools such as Power BI, Tableau, or Looker. Understanding of modern data architecture concepts such as Data Mesh and Lakehouse Architecture. Experience working in Agile/Scrum environments.

Strong analytical and problem-solving skills. Excellent verbal and written communication. Ability to work independently and collaboratively with cross-functional teams. Strong ownership and accountability. Ability to manage multiple priorities in a fast-paced environment. Preferred Candidate Profile

The client strongly prefers candidates with proven enterprise-level experience in Apache Airflow and dbt, including production deployment, orchestration design, dependency management, testing, and CI/CD integration.