Data Engineer

Job Description

Who we are looking for:

We’re looking for aData Engineer with strong experience in large-scale data environments to design and scale modern data platforms on Cloud Platform. This role requires hands-on expertise in building high-performance data pipelines and working closely with data scientists and analytics teams.

Responsibilities:

• Design, build, and maintain scalable data pipelines (batch and real-time)
• Develop and optimize data architectures on Google Cloud Platform (GCP)
• Work with tools such as BigQuery, Google Cloud Storage, Cloud Composer, and Cloud Functions
• Build and manage data transformation workflows using dbt
• Integrate data from multiple structured and unstructured sources
• Design and maintain conceptual and logical data models (ERDs, schemas)
• Ensure data quality, governance, security, and compliance
• Monitor and optimize pipeline performance, reliability, and cost
• Collaborate with data scientists and analysts to prepare datasets for analytics and machine learning
• Support the development and deployment of ML pipelines and data products
• Implement and manage real-time data streaming using Google Cloud Pub/Sub
• Troubleshoot data issues and continuously improve system performance

Qualifications:

• 10+ years of experience in data engineering and data modeling
• 3+ years working with large-scale big data environments (100TB+)
• Strong expertise in: SQL and Python, Data modeling (ERD, schema design),Data pipeline design and optimization
• Hands-on experience with GCP (recent 3–5 years), including: BigQuery, GCS, Cloud Functions, Composer
• Experience with dbt in production environments
• Strong understanding of modern data stack technologies (last 2–3 years)
• Experience working with Data scientists, Data analysts, Cross-functional engineering teams
• Knowledge of data mining, segmentation, and statistical analysis techniques
• Familiarity with data visualization tools

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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