Senior Data Engineer

Design and deliver robust, production-grade data-intensive applications and services that power business-critical use cases at scale. This role combines strong software engineering fundamentals with deep data engineering expertise and technical leadership.

Responsibilities

Design end-to-end systems (ingestion, processing, storage, serving) with minimal supervision; Build and maintain high-quality data products and pipelines on Spark and Databricks; Design event-driven architectures using Kafka and related technologies for real-time data processing; Build backend services and APIs that expose data capabilities reliably and securely; Build and optimize data models for analytical workloads (for example, dimensional modeling, data vault); Write clean, testable, and maintainable software in Scala (preferred) or Java; Drive architecture and design discussions with engineers, architects, and stakeholders; Coach and mentor junior engineers through code reviews, design sessions, and hands-on pairing; Improve engineering standards across testing, observability, CI/CD, reliability, and documentation; Deliver production-quality software with strong automated test coverage and clear quality gates; Use design reviews and lightweight ADR-style documentation for major technical decisions; Build observability into systems from day one (logs, metrics, tracing, alerts); Deliver through CI/CD with safe release and rollback strategies

Requirements

Bachelor’s degree in computer science, Computer Engineering, relevant technical field, or equivalent; Master’s degree preferred; 6+ years of professional software engineering experience, including substantial backend and data platform work; Strong programming background in Scala or Java (Scala preferred); Proven experience building distributed data pipelines with Spark and Databricks; Hands-on experience with Kafka in production systems; Strong understanding of distributed systems concepts and failure handling; Solid experience designing and developing APIs (REST and/or event-driven service interfaces); Strong knowledge of relational databases (for example PostgreSQL), data modeling, and query optimization; Demonstrated ability to design high-performance, concurrent systems; Experience leading technical design and architecture decisions across teams; Experience mentoring or coaching junior engineers

Nice to have

Practical experience with Flink and advanced stream processing patterns; Experience with cloud-native data platforms and infrastructure-as-code; Experience with building & deploying applications on Kubernetes; Experience with data governance, security, and compliance in data platforms; Familiarity with table formats and query engines in modern lakehouse ecosystems; Experience with performance profiling and JVM tuning