Sr. Data Engineer

About this Role

We are seeking a detail-oriented and highly skilled Data Engineer to design, build, and optimize data pipelines and infrastructure. You will play a key role in enabling data-driven decision-making across the organization by ensuring reliable, efficient, and scalable data systems. This role is ideal for someone who thrives at the intersection of software engineering and data architecture.

Key Responsibilities

  • Manage the quality assurance of collected data, ensuring both technical integrity (e.g., consistency, accuracy) and usability for client-facing time series analysis.
  • Build and maintain Big Data pipelines in an AWS cloud environment, optimizing for performance, scalability, and cost efficiency.
  • Drive innovation by researching and testing new technologies, proposing valuable features and architectural enhancements for both internal and client-facing use cases.
  • Lead automation initiatives by implementing CI/CD workflows and coding clean efficient, and well-documented solutions in Python.
  • Liaise with cross-functional teams to support data delivery and access, including optimizing data restitution via SQL, APIs, and architectural improvements.
  • Act as a core contributor to streaming data pipelines (e.g., Dataflow, Pub/Sub, Bigtable, BigQuery), ensuring reliability and performance in large-scale environments.

What you’ll Bring

  • Proven experience in Big Data engineering with 3+ years working with technologies such as Apache Beam, Spark, or Hadoop, and strong coding skills in Python, Java, or Golang.
  • Confidence in cloud-based environments (especially AWS) and performance/cost optimization of data workflows and streaming architectures.
  • Eagerness to learn, explore new tools, and develop scalable data infrastructure that delivers business value through clean and performant pipelines.
  • Good level of English (written and spoken) is essential; experience with Clickhouse is a plus.
Job Category: Engineering
Job Type: Full Time
Job Location: Hybrid

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