Data Architectural Specialist

2 days ago


Tiruppur, Tamil Nadu, India beBeeDataEngineer Full time ₹ 15,00,000 - ₹ 25,00,000
Job Title

Senior Data Engineer

  • Main Responsibilities:
  • Data Pipeline Development:
    • Design and develop scalable data pipelines using Python and GCP services such as Vertex AI, BigQuery, and Dataflow.
    • Ensure high-throughput and low-latency processing of massive datasets efficiently.
  • Data Filtering and Curation:
    • Optimize data ingestion and transformation for downstream models.
    • Implement intelligent scanning mechanisms to filter out relevant data for AI/ML models.
  • Ai/ml Integration:
    • Leverage GenAI models under the Vertex AI umbrella.
    • Build and fine-tune custom models when LLMs are cost-prohibitive or less effective.
    • Design multi-layered model pipelines balancing accuracy, cost, and performance.
  • Cloud Infrastructure:
    • Architect scalable solutions primarily on GCP services.
    • Azure knowledge is a plus but not mandatory.
    • Experience in building robust monitoring systems.
  • Performance Optimization:
    • Ensure real-time, low-latency processing for high-volume workloads.
    • Optimize GPU/CPU-intensive environments to manage cost and efficiency.
  • Collaboration and Ownership:
    • Work closely with data scientists, ML engineers, and solution architects.
    • Take end-to-end ownership of assigned tasks and deliverables.
    • Collaborate with global teams and manage timezone overlap when required.
    Required Skills and Qualifications
    • Programming: Expert-level Python.
    • Data Engineering: Hands-on experience with streaming pipelines and large-scale data ingestion frameworks.
    • Ai/ml Expertise: Experience integrating and fine-tuning LLMs and GenAI models. Comfortable working with custom model development where LLMs cannot be applied. Familiarity with OpenAI, Gemini, Vertex AI, or equivalent platforms.
    • Cloud: GCP (mandatory) — experience with Vertex AI, BigQuery, GKE, Cloud Run, PostgreSQL, Dataflow, Pub/Sub, etc. Azure experience is a plus.
    • Scalability and Low Latency: Proven ability to design and implement high-performance, distributed data solutions.
    • High-Volume Data Processing: Experience processing massive datasets efficiently within strict timeframes.
    Good to Have
    • MLOps and deploying models at scale.
    • Data governance and compliance when working with sensitive data.
    • Event-driven architectures and microservices.


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