Senior Data Engineer

We are looking for a Senior Data Engineer to lead the design and development of robust, scalable, and high-performance data pipelines and systems. You will work closely with data architects, analysts, and business stakeholders to ensure data availability, quality, and usability across the organization.

Key responsibilities:

• Design and implement an agile AI-driven development framework for data pipelines and Data Warehouses (DWH) using Claude Code and/or Cursor;

• Design, build, and maintain reliable streaming and batch ETL/ELT data pipelines and workflows in GCP environments;

• Develop and optimize data ingestion processes from various structured and unstructured sources;

• Collaborate with Data Architects and Analysts to ensure alignment with data models, data governance policies, and performance standards;

• Implement best practices in data engineering, ensuring scalability, reusability, and data quality.

• Build and maintain data lakes, data warehouses, and analytical data marts to support reporting, BI, and advanced analytics using dbt Core;

• Integrate data validation, monitoring, and quality checks into pipelines using Google Cloud Monitoring and Cloud Logging;

• Optimize the performance of data jobs and troubleshoot issues within data pipelines and processing layers;

• Ensure data security, including encryption, access control, and data privacy compliance;

• Participate in code reviews, technical mentoring, and continuous improvement initiatives.

Required Skills & Experience:

• 5+ years of experience in data engineering, working with large-scale distributed systems;

• Strong expertise in SQL, Python, and data processing frameworks (Apache Beam, Spark, Kafka);

• Experience building data pipelines using cloud-native technologies, particularly within Google Cloud Platform (GCP) (BigQuery, Dataflow, Cloud Run, Pub/Sub, Cloud Storage, Cloud Composer, Airbyte, and dbt Core);

• Solid understanding of ETL/ELT processes, data modeling, and schema design;

• Familiarity with workflow orchestration tools such as Cloud Workflows and Cloud Compose;

• Proven experience implementing data quality assurance, monitoring, and error handling mechanisms;

• Hands-on experience with CI/CD practices (Azure DevOps is highly desirable) and Infrastructure-as-Code (IaC) tools like Terraform to design DataOps and MLOps pipelines;

• Knowledge of data security practices, including encryption at rest/in transit, IAM/RBAC, and compliance frameworks (GDPR, HIPAA, etc.);

• Excellent problem-solving, debugging, and performance-tuning skills;

• Ability to collaborate in cross-functional teams and communicate effectively with both technical and non-technical audiences;

• Fluent English.