Data Engineer

4 weeks ago

Erode, Tamil Nadu, India AgileEngine Full time
Senior Data Engineer (AI/ML |
Python | GCP ) - WFH

THIS IS FULLY REMOTE WORKING OPPORTUNITY.

WE NEED IMMEDIATE JOINERS or someone who can join in less than 1 month.

If you are interested and fulfill the below mentioned criteria then please share below information.

1. EMAIL ID
2. YEARS OF RELEVANT EXPERIENCE.
3. UPDATED RESUME.
4. CCTC/ECTC
5. Notice period

*Key Responsibilities*

1. Design & Develop Scalable Data Pipelines
  • Build high-throughput, low-latency pipelines to process massive datasets efficiently.
  • Ensure pipelines can handle 5–10 TB of structured and unstructured data at scale.
2. Data Filtering & Curation
  • Optimize data ingestion and transformation for downstream models.
  • Implement intelligent scanning mechanisms to filter out relevant data for AI/ML models
3. AI/ML Integration
  • Leverage GenAI models (e.g., Gemini Pro, OpenAI, GPT) 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.
4. Cloud Infrastructure
  • Architect scalable solutions primarily on GCP (Vertex AI, BigQuery, GKE, Cloud run, PostgreSQL, Dataflow, Pub/Sub).
  • Azure knowledge is a plus but not mandatory.
  • Experienced in building robust monitoring system.
5. Performance Optimization
  • Ensure real-time, low-latency processing for high-volume workloads.
  • Optimize GPU/CPU-intensive environments to manage cost and efficiency.

6. Collaboration & Ownership
  • Work closely with data scientists, ML engineers, and solution architects.
  • Take end-to-end ownership of assigned tasks and deliverables, working independently where needed.
  • Collaborate with global teams and manage 3–4 hours of timezone overlap when required.
*Required Skills & Qualifications*

1. Programming

* Expert-level Python (mandatory).

2. Data Engineering:

* Hands-on experience with streaming pipelines, and large-scale data ingestion frameworks.

3. 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.

4. Cloud:

* GCP (mandatory) — experience with Vertex AI, BigQuery, GKE, Cloud Run, PostgreSQL, Dataflow, Pub/Sub, etc.
* Azure experience is a plus.

5. Scalability & Low Latency:

* Proven ability to design and implement high-performance, distributed data solutions.

6. High-Volume Data Processing:

* Experience processing massive datasets efficiently within strict timeframes.

*Good to Have*
  • Experience with MLOps and deploying models at scale.
  • Knowledge of data governance and compliance when working with sensitive data.
  • Hands-on exposure to event-driven architectures and microservices.

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