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Xebia

Lead Data Engineer - Scala/Spark

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Job Description

Job Title : Lead Data Engineer - Scala/Spark

Job location : Bengaluru

Exp Range : 6-12 years

Notice Period : immediate - 15 days

We are seeking a Senior Data Engineer with deep expertise in Scala-based Spark development and end-to-end deployment of data pipelines on Kubernetes cluster, orchestrated via Airflow. The ideal candidate should have a strong software engineering foundation, excellent understanding of distributed systems, proficient in software design, modern project/code structuring skills, with good understanding on CI/CD processes and implementation which enables them to deliver reliable, scalable and robust data solutions. Should have overall experience of minimum 6-8 years with minimum 5Years in Hadoop, Spark.

Key Responsibilities: • Design & implement robust, scalable, batch & real-time data engineering solutions using Apache Spark (Scala) & Spark structure streaming. • Architect well-structured Scala projects using reusable, modular, and testable codebases aligned with SOLID principles and clean architecture principles & practices. • Develop, Deploy & Manage Spark jobs on Kubernetes clusters, ensuring e icient resource utilization, fault tolerance, and scalability. • Orchestrate data workflows using Apache Airflow — manage DAGs, task dependencies, retries, and SLA alerts. • Write and maintain comprehensive unit tests and integration tests for Pipelines / Utilities developed. • Work on performance tuning, partitioning strategies, and data quality validation. • Use and enforce version control best practices (branching, PRs, code review) and continuous integration (CI/CD) for automated testing and deployment. • Write clear, maintainable documentation (README, inline docs, docstrings). • Participate in design reviews and provide technical guidance to peers and junior engineers

Technical Skills: Primary: • Languages: Scala, Java • Big Data Orchestration: Airflow, Spark on Kubernetes, Yarn, Oozie • Big Data Processing: Hadoop, Kafka, Spark & Spark Structured Streaming. • Experience on SOLID & DRY principles with Good Software Architecture & Design implementation experience • Advanced Scala experience (e.g. Functional Programming, using Case classes, Complex Data Structures & Algorithms) • Proficient in developing automated frameworks for unit & integration testing. • Experience with Docker and Helm and related container technologies. • Proficient in deploying and managing Spark workloads on Kubernetes clusters. • Experience in evaluation and implementation of Data Validation & Data Quality • Devops experience in Jenkins, Maven, Github, Github actions, CI/CD

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Job ID: 150634387