Senior Data Engineer - Big-data

• Proven experience leading data engineering teams, including distributed teams across multiple geographies and time zones.
• Effective in managing cross-team collaboration with architects, product managers, and operations.
• Scala and Python
• Apache Spark (batch & streaming) – must!
• Deep knowledge of HDFS internals and migration strategies.
• Experience with Apache Iceberg (or similar table formats like Delta Lake / Apache Hudi) for schema evolution, ACID transactions, and time travel.
• Running Spark and/or Flink jobs on Kubernetes (e.g., Spark-on-K8s operator, Flink-on-K8s).
• Experience with distributed blob storages like Ceph or AWS S3 and similar
• Building ingestion, transformation, and enrichment pipelines for large-scale datasets.
• Infrastructure-as-Code (Terraform, Helm) for provisioning data infrastructure.
• Strong communication skills
  
  

Essential Functions

• Lead and mentor a team of data engineers, providing technical direction and career guidance.
• Define the target data platform architecture for migrating from on-prem HDFS/Hive to Cloud Object Storage (e.g., AWS S3, Azure Data Lake Storage, or GCP Cloud Storage).
• Select and integrate cloud-based compute and query engines (e.g., Spark).
• Lead the design of ingestion, transformation, and storage patterns optimized for scalability, cost-efficiency, and performance in the cloud.
• Define security, encryption, and compliance controls for sensitive enterprise data in the cloud.
• Develop and own the migration roadmap, including phased transition from on-prem to cloud while minimizing business disruption.
• Oversee data migration strategies (bulk historical loads, incremental sync, and cutover).
• Define and enforce coding standards, CI/CD pipelines, and automated testing for data pipelines.
• Partner with Data Architects, Cloud Engineers, and Security teams to align platform design with enterprise standards.
  
  

Qualifications

• Strong hands-on experience in Scala and Python.
• Expertise in Apache Spark (batch and streaming).
• Familiarity with Cloud - AWS
• Solid understanding of HDFS internals and migration strategies.
• Experience with Apache Iceberg, Delta Lake, or Apache Hudi.
• Familiarity with distributed blob storage (e.g., S3, Ceph).
• Proficiency in Infrastructure-as-Code tools like Terraform and Helm.
  
  

Would be a plus

• Experience with Apache Flink
• Apple experience preferred (to enable him/her to get up to speed on our tooling set quickly and more independently)
  
  

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.

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