Senior Data Engineer

Job Title:

Employment Type:

Experience Required:

About The Role

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines using SQL and Python.
• Orchestrate data workflows using Dagster (and legacy Airflow).
• Collaborate across teams to enable self-service analytics and meet data requirements.
• Implement streaming, batch, and Change Data Capture (CDC) data flows.
• Use DBT for data transformation and modeling aligned to business needs.
• Monitor data quality, troubleshoot issues, and optimize pipelines.
• Ensure adherence to security, privacy, and compliance standards.
  

Required Skills & Experience

• 4+ years of data engineering experience.
• Strong SQL skills and hands-on experience with cloud data warehouses (Snowflake, BigQuery, Redshift).
• Expertise in ETL/ELT processes, batch, and streaming data pipelines.
• Proficient with AWS data services (S3, DMS, Glue, Athena).
• Experience with DBT for data modeling and transformation.
• Fluent in English communication.
  

Preferred Qualifications

• Experience with additional AWS services: EC2, ECS, EKS, VPC, IAM.
• Familiarity with Infrastructure as Code (Terraform, Terragrunt).
• Proficiency in Python for data engineering tasks.
• Knowledge of orchestration tools such as Dagster, Airflow, or AWS Step Functions.
• Understanding of pub-sub and streaming frameworks (AWS Kinesis, Kafka, SQS, SNS).
• Experience with CI/CD pipelines and automation.
  

Tech Stack Highlights

• Languages: SQL, Python
• Pipeline Orchestration: Dagster, Airflow
• Data Stores: Snowflake, Clickhouse
• Cloud Platforms: AWS (ECS, EKS, DMS, Kinesis, Glue, Athena, S3)
• ETL Tools: FiveTran, DBT
• Infrastructure: Docker, Kubernetes, Terraform with Terragrunt