Data Engineer

We are seeking a Data Engineer to support the modernization and scaling of cloud data platforms and high-volume ELT pipelines for global enterprise retail and consumer leaders. In this role, you will design, build, and optimize end-to-end batch and streaming pipelines, consolidate complex business KPIs into single-source-of-truth data models, and improve warehouse query performance. Working alongside cross-functional cloud architecture and analytics teams, you will leverage modern cloud platforms, big data frameworks, and workflow orchestrators to drive business-critical data solutions. Responsibilities
• Design, build, and maintain production-grade ELT/ETL data pipelines to ingest, transform, and consolidate large-scale data from multiple enterprise sources.
• Optimize data warehouse architectures, table structures, and query performance for business-critical reporting and advanced analytics.
• Develop data processing workflows using Python, SQL, and big data processing frameworks (such as Apache Spark / PySpark).
• Automate data pipeline scheduling, monitoring, and quality validation using modern orchestration tools (Airflow or Kubeflow).
• Establish reliable API and cloud database connectors while collaborating with business and technical stakeholders to adapt to evolving analytics requirements. Requirements
• Proven hands-on experience as a Data Engineer building and maintaining complex ELT/ETL data pipelines in enterprise environments.
• Strong proficiency in Python and advanced SQL for complex data transformations, aggregations, and performance tuning.
• Hands-on experience developing data pipelines on Google Cloud Platform (GCP) or Microsoft Azure (including services like BigQuery, GCS, Azure Data Factory, or Azure Data Lake).
• Practical experience working with big data processing frameworks (Apache Spark / PySpark) and pipeline orchestrators (Apache Airflow or Kubeflow).
• Solid background in containerization (Docker, Kubernetes) and modern CI/CD practices (GitHub Actions, Azure DevOps, or similar). Nice to have
• Experience with Databricks for unified analytics and large-scale data transformation.
• Exposure to search, indexing, or vector storage technologies (such as Elasticsearch).
• Active industry cloud certifications (GCP Professional Data Engineer or Azure Data Engineer Associate).

We offer
• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package
- medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.