Sr. DevOps Engineer

We are seeking a skilled Data Engineer with 2-4 years of experience to design, build, and maintain scalable data pipelines and infrastructure. You will work with modern data technologies to enable data-driven decision making across the organisation.

Design and implement ETL/ELT pipelines using Apache Spark and orchestration tools (Airflow/Dagster). Build and optimize data models on Snowflake and cloud platforms. Collaborate with analytics teams to deliver reliable data for reporting and ML initiatives. Monitor pipeline performance, troubleshoot data quality issues, and implement testing frameworks. Contribute to data architecture decisions and work with cross-functional teams to deliver quality data solutions.

• 2-4 years of experience in data engineering or related field
• Strong proficiency with Snowflake including data modeling, performance optimisation, and cost management
• Hands-on experience building data pipelines with Apache Spark (PySpark)
• Experience with workflow orchestration tools (Airflow, Dagster, or similar)
• Proficiency with dbt for data transformation, modeling, and testing
• Proficiency in Python and SQL for data processing and analysis
• Experience with cloud platforms (AWS, Azure, or GCP) and their data services
• Understanding of data warehouse concepts, dimensional modeling, and data lake architectures

• Experience with infrastructure as code tools (Terraform, CloudFormation)
• Knowledge of streaming technologies (Kafka, Kinesis, Pub/Sub)
• Familiarity with containerisation (Docker, Kubernetes)
• Experience with data quality frameworks and monitoring tools
• Understanding of CI/CD practices for data pipelines
• Knowledge of data catalog and governance tools
• Advanced dbt features including macros, packages, and documentation
• Experience with table format technologies (Apache Iceberg, Apache Hudi)

• Data Warehouse:

  Snowflake

• Processing:

  Apache Spark, Python, SQL

• Orchestration:

  Airflow/Dagster

• Transformation:

  dbt

• Cloud:

  AWS/Azure/GCP

• Version Control:

  Git

• Monitoring:

  DataDog, Grafana, or similar