Platform Engineer - Neo4j, Cypher & Python with IT Company - Remote

Exp - 4-8 yrs

Work Mode - Remote

Key Responsibilities

• Build data ingestion connectors for structured, unstructured, licensed and open-source datasets.
• Develop reliable data pipelines with data contracts, schema validation, data-quality checks, error handling and quarantine mechanisms.
• Design point-in-time data storage using Delta Lake, Parquet and object storage, ensuring historical revisions and publication timestamps are preserved.
• Implement historical data retrieval, as-of reads, data lineage and reproducible datasets without future-data leakage.
• Develop reference data and identity-resolution systems across multiple data sources.
• Own the graph data layer, including property-graph modelling, ontology-driven schema generation and schema-as-code.
• Build, deploy and operate production Neo4j databases, including data loading, Cypher query optimisation, indexing and performance monitoring.
• Generate deterministic graph projections for historical dates and integrate graph features with downstream data and ML workflows.
• Build and maintain cloud infrastructure, containerised jobs, orchestration workflows, CI/CD pipelines, monitoring and automated testing.
• Use AI coding agents to accelerate development while maintaining code quality, testing, documentation and engineering standards.

Mandatory Skills

• Strong hands-on experience in

  Python and SQL

  .
• Experience with data engineering, ETL/ELT pipelines, data contracts, schema evolution and data-quality validation.
• Practical understanding of point-in-time data, historical snapshots, publication lags, data revisions and reproducibility.

• Production experience with Neo4j and Cypher

  , including graph modelling, data ingestion, query optimisation and managed database operations.
• Experience with Pandas, Polars or DuckDB.
• Familiarity with PostgreSQL, Parquet/Delta Lake and object storage.
• Experience with Docker, Terraform, GitHub Actions or equivalent CI/CD tools.
• Hands-on experience with at least one major cloud platform; GCP is preferred.
• Experience with Dagster, Airflow or similar workflow orchestration tools.
• Familiarity with MLflow, logging, monitoring, secrets management and automated testing.
• Practical experience using AI coding agents such as Claude Code, Codex CLI, Cursor or equivalent tools in daily development workflows.