Data Engineer - Apache Airflow

Job Description – Data Engineer
Position-Data Engineer
Experience-5 – 10 Years
LOCATION: NEWZEALAND (ON-SITE OPPORTUNITY)
Job Summary
We are seeking an experienced Data Engineer with strong expertise in building scalable and high-performance data platforms. The ideal candidate will have hands-on experience with Apache Airflow, Apache Spark, PySpark, Scala, Databricks, Docker, and Advanced SQL, with a proven track record of developing and optimizing large-scale data pipelines and ETL processes.
Key Responsibilities
Design, develop, and maintain scalable data pipelines and data processing frameworks.
Build and orchestrate ETL/ELT workflows using Apache Airflow.
Develop data engineering solutions using Apache Spark, PySpark, and Scala.
Leverage Databricks for large-scale data processing, optimization, and analytics.
Write, optimize, and troubleshoot complex SQL queries involving:
Inner, Left, Right, and Full Joins
Self Joins
CTEs and Subqueries
Window Functions
Query Performance Tuning
Develop, deploy, and manage containerized applications using Docker.
Collaborate with cross-functional teams to gather requirements and deliver robust data solutions.
Implement data quality checks, monitoring, and performance tuning.
Ensure data governance, security, and compliance standards are maintained.
Troubleshoot and resolve production issues related to data pipelines and processing jobs.
Mandatory Skills
Apache Airflow – DAG creation, workflow orchestration, scheduling, and monitoring.
Apache Spark – Distributed data processing and performance optimization.
PySpark – ETL development, transformations, and data engineering.
Scala Programming – Strong hands-on development experience with Spark/Scala applications.
Databricks – Notebooks, workflows, Delta Lake, and cluster management.
Advanced SQL
Strong expertise in Joins (Inner, Outer, Left, Right, Full, Self)
Window Functions
Query Optimization
Data Modeling Concepts
Performance Tuning
Docker
Containerization
Image Creation and Management
Docker Compose
Deployment and Troubleshooting
Python Programming
Git Version Control
Preferred Skills
Delta Lake
Azure, AWS, or GCP
Kafka or Streaming Technologies
CI/CD Pipelines (Azure DevOps, Jenkins, GitHub Actions)
Data Warehousing Concepts
Linux/Unix Administration
Lakehouse Architecture
Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
5–10 years of experience in Data Engineering and Big Data technologies.
Strong expertise in Spark ecosystem and distributed computing.
Experience building enterprise-scale data platforms and ETL solutions.
Excellent analytical, problem-solving, and communication skills.

Work arrangement
No