Advanced Data Architect

2 days ago

India Spydra Full time

At Spydra, we are seeking an experienced Advanced Data Architect to lead the development of advanced systems for observability and AI-driven analytics.

We are looking for someone with a strong background in designing data correlation solutions, implementing predictive models for anomaly detection, and creating proactive monitoring frameworks to enhance operational reliability and minimize system failures.

Data Correlation and Insight Generation:

  • Develop robust solutions to correlate data across multiple observability layers.
  • Integrate diverse data streams, such as metrics, logs, traces, and code performance, to effectively diagnose root causes.

Anomaly Detection and Prediction:

  • Build and deploy machine learning models to identify and predict anomalies.
  • Provide early failure warnings to prevent outages, empowering operational teams to take preemptive action.

Data Pipeline and Architecture Development:

  • Design and maintain scalable data pipelines to handle large-scale observability datasets (timeseries data).
  • Optimize real-time data processing, storage, and retrieval for performance and efficiency.

Collaboration and Visualization:

  • Partner with cross-functional teams, including DevOps and SRE, to enhance observability practices and predictive capabilities.
  • Create user-friendly dashboards and visual reports for effective communication of insights.

Continuous Optimization:

  • Refine and enhance observability tools and systems for improved precision, speed, and scalability.
  • Stay informed on the latest trends and technologies in data engineering, observability, and machine learning.

Required Expertise:

  • Comprehensive understanding of observability tools and frameworks (e.g., Prometheus, Grafana, Splunk, ELK, Datadog).
  • Strong proficiency in analyzing metrics, logs, and traces, particularly timeseries data.

Data Engineering Proficiency:

  • Hands-on experience in developing robust data pipelines and correlation frameworks.
  • Expertise in cloud-native observability platforms and distributed systems.

Machine Learning Skills:

  • Knowledge of building and implementing predictive analytics models for anomaly detection.
  • Familiarity with ML tools and frameworks like TensorFlow, PyTorch, or scikit-learn.

Programming and Cloud Experience:

  • Advanced skills in programming languages such as Python, Java, or Go.
  • Experience working with cloud platforms (AWS, GCP, Azure) and automation technologies.

Collaboration and Communication:

  • Strong problem-solving skills and ability to work across teams.
  • Effective communicator with a knack for presenting technical insights clearly.

With a salary range of $150,000 - $200,000 per annum, this role offers a competitive compensation package. Our ideal candidate will have a deep understanding of data engineering principles and be able to apply them to drive business outcomes.

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