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.

    • Bachelor’s degree in computer science, Computer Engineering, relevant technical field, or equivalent; Master’s degree preferred.

Roles & Responsibility:

  • 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.

Skills

  • 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.

Good 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.

Collaboration Scope:

  • Partner with product, platform, and domain teams to translate requirements into resilient technical solutions.
  • Work closely with architects and technical leadership to shape platform direction.
  • Support incident response and root-cause analysis for critical production issues.
  • Help define roadmaps that align business priorities with engineering sustainability.

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