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

Seventh Contact Hiring Solutions; Pune District; Teletrabalho; INR 600 000 - 900 000; Tempo integral

Resumo da oferta

Seventh Contact Hiring Solutions is seeking a data engineer to build robust data ingestion, graph data layer and production Neo4j solutions. The role emphasizes Delta Lake/Parquet storage, as-of reads, data lineage and reproducible datasets, with graph analytics driving ML workflows.

You will design and operate cloud infrastructure, containerised jobs, orchestration workflows, CI/CD pipelines and AI-assisted development using Python and SQL on GCP.

Qualificações

• 4–8 years of relevant work experience.

Responsabilidades

• 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.

Conhecimentos

Python

SQL

Data engineering

ETL/ELT pipelines

Data contracts

Schema evolution

Data-quality validation

Cypher/Neo4j

Pandas/Polars/DuckDB

Cloud platforms (GCP preferred)

CI/CD (Docker/Terraform/GitHub Actions

Workflow orchestration (Dagster/Airlf​

MLflow/logging/monitoring

AI coding agents integration

Ferramentas

Neo4j

Cypher

Docker

Terraform

GitHub Actions

Dagster

Airflow

MLflow

Claude Code

Codex CLI

Cursor

Delta Lake

Parquet

Polars

DuckDB

PostgreSQL

Descrição da oferta de emprego

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.