Senior Big Data Engineer
Location: Remote from Turkey
Employment Type: Full-Time Contractor (sole proprietor)
Overlap until 11 am PST
Join our global team of leading big data engineers to design, build, and verify high-scale data pipelines using the latest versions of Scala and Spark. In this role, you will ensure the statistical precision of reports derived from massive datasets while actively collaborating on modern Kubernetes infrastructure and CI/CD pipelines.
Essential functions
Architect, code, and maintain robust batch and real-time data pipelines using the latest versions of Scala and Spark/Spark Streaming to process massive datasets.
Implement and rigorously verify complex algorithmic jobs (utilizing advanced SparkSQL) to guarantee that generated reports return flawless, precise statistics for critical stakeholder decision-making.
Work with containerized big data infrastructure, managing datasets within Hive and Apache Iceberg table formats while ensuring optimal execution of Spark on Kubernetes clusters.
Take ownership of the data infrastructure lifecycle by implementing CI/CD pipelines and automated workflows (via Airflow) to streamline deployment, resource allocation, and job orchestration.
Partner closely with leading big data and infrastructure engineers across Europe and overseas in an agile, cross-functional environment to continuous improve data delivery and system reliability.
Qualifications
Strong proficiency in Scala for building robust, scalable, and production-grade data pipelines.
Deep expertise in Apache Spark and Spark Streaming for both large-scale batch and real-time event processing.
Hands-on experience working with Hive metastores and open table formats like Apache Iceberg to manage large-scale data lakes.
Mastery of SQL (specifically SparkSQL), with advanced knowledge of window functions, complex “group by” operations and query optimization.
Experience designing, scheduling, and monitoring complex data workflows using Apache Airflow.
Solid conceptual understanding of Kubernetes (K8s), specifically how Spark executes on Kubernetes clusters (e.g., managing resource allocation, drivers, and executors).
Would be a plus
Experience with Apache Flink for real-time stream processing and stateful computations.
Familiarity utilizing Claude (Anthropic) or similar LLMs for code generation, query optimization, or workflow automation.
We offer
Opportunity to work on bleeding-edge projects
Work with a highly motivated and dedicated team
Competitive salary
Flexible schedule
Professional development opportunities
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.Apply to the position
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Grid Dynamics is an equal opportunity employer. We are committed to creating an inclusive environment for all employees during their employment and for all candidates during the application process.
All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. All employment is decided on the basis of qualifications, merit, and business need.