Data Engineer - SQL - Remote (Permanent)

Experience: 4.00 + years

Confidential (based on experience)

Shift : (GMT+05:30) Asia/Kolkata (IST)

Opportunity Type : Remote

Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Proplens)

(*Agent Workflows, CCPA) and enterprise security patterns, Experience with Machine Learning and/or Computer Vision, Knowledge of data-governance (GDPR, Prompt Engineering, Data Engineering, DuckDB, Python

Data Engineer

We are seeking a versatile Data Engineer with 4-7 years of experience to own end-to-end data pipelines for downstream AI agent applications. You'll design data models and transformations, build scalable ETL/ELT workflows, and collaborate on ML model deployment, while learning fast and working on the AI agent space.

Data Modeling & Pipeline development

Define and implement logical/physical data models and schemas

Develop schema mapping and data dictionary artifacts for cross-system consistency

Build, test, and maintain robust ETL/ELT workflows using Spark (batch & streaming)

Automate data ingestion from diverse sources (Databases, APIs, files, Sharepoint/document management tools, URLs)

Gen AI Integration

Collaborate with AI engineers to enrich data for agentic workflows

Instrument pipelines to surface real-time context into LLM prompts

ML Model Deployment Support (Secondary role)

Package and deploy ML models (e.g., via MLflow, Docker, or Kubernetes)

Integrate inference endpoints into data pipelines for feature serving

Implement monitoring, alerting, and logging (data quality, latency, errors)

Apply access controls and data privacy safeguards (e.g., Develop automated testing, versioning, and deployment (Azure DevOps, GitHub Actions, Airflow)

Required Skills & Experience

• 5 years in Data Engineering or similar role, with exposure to ML modeling pipelines
• Proficiency in Python, dlt for ETL/ELT pipeline, duckDB for analytical in-process analysis, dvc for managing large files efficiently.
• Solid SQL skills and experience designing and scaling relational databases.
• Familiarity with non-relational column based databases.
• Azure Data Factory)
• Experience deploying ML artifacts using MLflow, Docker, or Kubernetes
• Strong Dev Ops/Git workflows and CI/CD (CircleCI and Azure DevOps)

Bonus skillsets:

Experience with Machine Learning and/or Computer Vision

Knowledge of data-governance (GDPR, CCPA) and enterprise security patterns

Steep learning opportunities in real world enterprise production use-cases

Remote work with quarterly meet-ups

Step 3: Increase your chances to get shortlisted & meet the client for the Interview!

Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today.