About DubaiData DubaiData is an AI-powered data intelligence platform focused on transforming large-scale structured and unstructured data into intelligent, actionable insights. We build cloud-native data platforms, AI-powered analytics solutions, and scalable data infrastructure that powers our growing suite of data products.

As our platform continues to expand, we are looking for an experienced Data Engineer to help build the data foundation that powers our AI applications, analytics platform, and intelligent data products.

Role Overview The Data Engineer will be responsible for designing, building, and maintaining DubaiData's cloud-native data platform on Google Cloud Platform (GCP). This role involves developing scalable ETL/ELT pipelines, managing large-scale datasets, implementing modern data architectures, and enabling high-quality, analytics-ready data for AI models and business intelligence.

You will work closely with AI Engineers, Product Managers, and Software Engineers to build reliable data infrastructure that supports both internal operations and customer-facing products.

Key Responsibilities Design, build, and maintain scalable ETL/ELT pipelines for ingesting structured and unstructured data from multiple global data sources. Develop cloud-native data engineering solutions using Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, Cloud Composer, Cloud Run, Pub/Sub, and Dataproc. Build and manage scalable data lakes, data warehouses, and modern lakehouse architectures that support AI, analytics, reporting, and product development.

Implement medallion architecture (Bronze, Silver, and Gold layers) to create clean, governed, and reusable datasets. Design efficient dimensional data models using Star Schema and Snowflake Schema to support analytical workloads. Develop robust Python and SQL-based data processing pipelines for extraction, transformation, validation, and orchestration.

Integrate data from APIs, databases,



flat files, third-party platforms, web services, event streams, and other heterogeneous data sources. Ensure high standards of data quality, reliability, security, observability, and performance across all data pipelines.

Optimize

BigQuery performance and cloud infrastructure to balance scalability, efficiency, and cost. Maintain source-to-target mappings, data lineage, documentation, and operational runbooks. Collaborate closely with AI Engineers to prepare high-quality datasets for machine learning, LLMs, and intelligent automation workflows. Work with product and engineering teams to translate business requirements into scalable data solutions.

Required Qualifications 3+ years of professional experience in Data Engineering, ETL/ELT development, or a related field. Solid expertise in Python and SQL, including complex queries, performance optimization, and large-scale data processing.

Experience building scalable ETL/ELT pipelines in production environments. Strong understanding of relational databases, data warehouses, dimensional modelling, and modern data architecture.

Experience designing and maintaining data lakes, data warehouses, Star Schema, Snowflake Schema, and Medallion Architecture. Hands-on experience with Google Cloud Platform, particularly: BigQuery Cloud Storage Cloud Run Dataflow Pub/Sub Cloud Composer Dataproc (preferred) Experience integrating structured, semi-structured, and unstructured data from multiple data sources. Strong understanding of data governance, data quality, monitoring, and production support.





Experience with Git and collaborative software development practices.

Preferred Qualifications Experience building data platforms for AI, machine learning, or large-scale analytics applications. Familiarity with vector databases, embeddings, semantic search, or Retrieval-Augmented Generation (RAG) pipelines.

Experience working with modern data formats such as Parquet, Avro, and JSON. Familiarity with Apache Airflow or Cloud Composer for workflow orchestration.

Experience with Docker, containerized applications, and CI/CD pipelines. Exposure to Infrastructure as Code (Terraform or similar) is an advantage.

Google Cloud Professional Data

Engineer certification is a plus.

Ideal Candidate Profile

We're looking for someone who enjoys building scalable data platforms and solving complex data engineering challenges.

The ideal candidate

Has strong problem-solving and analytical skills. Writes clean, maintainable, and production-ready Python and SQL code. Enjoys working with large datasets and modern cloud technologies. Understands how reliable data infrastructure enables AI and intelligent analytics.

Is proactive, collaborative, and comfortable working in a fast-paced startup environment. Takes ownership of projects and continuously looks for ways to improve data quality, scalability, and operational efficiency. What You'll Work On As a Data Engineer at DubaiData, you'll contribute to building the core data infrastructure behind our AI-powered platform, including:

Global data ingestion and integration pipelines Cloud-native data lakes and data warehouses AI-ready datasets for machine learning and LLM applications Intelligent data processing and transformation workflows Analytics and reporting infrastructure Scalable data architecture on Google Cloud Platform High-performance data pipelines powering DubaiData's growing suite of AI and data products

📌 Data Engineer (India)
🏢 DubaiData
📍 India