Data Systems Engineer

Oxford Data Plan; Indore District; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Oxford Data Plan is seeking a self-driven Data Systems Engineer to build and improve data systems supporting products and research workflows. The role spans production Python, data pipelines, databases and internal tooling.

You will own technical problems, work independently through implementation, and collaborate with data scientists, researchers and engineers to translate requirements into practical solutions.

Qualifications

• 2-4+ years of professional experience in software engineering, data engineering or a related technical role.
• Experience with PySpark, Apache Iceberg, dbt or modern lakehouse technologies.
• Experience building internal Python packages, libraries or CLI tools.
• Experience with AWS, GCP or Azure.
• Strong Python skills, with clean, reusable production code.
• Strong SQL skills with PostgreSQL, MySQL or similar.
• Experience building data pipelines and working with structured datasets.
• Good understanding of data modelling, data quality, failure handling and operational reliability.
• Experience in production cloud environments and with CI/CD.

Responsibilities

• Design, build and maintain production data pipelines and internal Python libraries used across data and research workflows.
• Support migration and modernisation of existing data pipelines and systems.
• Contribute to data modelling, transformations and downstream data marts.
• Improve the reliability of data systems through validation, testing, monitoring, logging and alerting.
• Build reusable tooling for common data and research workflows.
• Investigate and resolve data, application and pipeline issues across production systems.
• Contribute to deployment automation, environment management, CI/CD and infrastructure-as-code.
• Collaborate with data scientists, researchers and engineers to translate requirements into scalable technical solutions.
• Maintain strong engineering standards through testing, documentation, code review and clear technical communication.
• Use AI tooling effectively while understanding, reviewing and defending the code you ship.

Skills

Python

SQL

Data pipelines

Cloud platforms

Debugging

Collaboration

Code reviews

AI tooling

Tools

PySpark

Apache Iceberg

dbt

Docker

Airflow

Terraform

Grafana

Job description

Job Description:

We are looking for a self-driven Data Systems Engineer to help build and improve the data systems that support our products and research workflows.

This is a hands-on technical role spanning production Python, data pipelines, databases and internal tooling. You will work on the libraries and infrastructure that underpin our data products, improve how data is stored and processed, and help make our systems more reliable, scalable and easier for others to work with.

You should be comfortable taking ownership of well-defined technical problems, working independently through implementation, and collaborating with data scientists, researchers and engineers to turn requirements into practical solutions.

Roles and Responsibilities

• Design, build and maintain production data pipelines and internal Python libraries used across data and research workflows.
• Support migration and modernisation of existing data pipelines and systems.
• Contribute to data modelling, transformations and downstream data marts.
• Improve the reliability of data systems through validation, testing, monitoring, logging and alerting.
• Build reusable tooling that makes common data and research workflows simpler and more reliable.
• Investigate and resolve data, application and pipeline issues across production systems.
• Contribute to deployment automation, environment management, CI/CD and infrastructure-as-code.
• Collaborate with data scientists, researchers and engineers to translate requirements into scalable technical solutions.
• Maintain strong engineering standards through testing, documentation, code review and clear technical communication.
• Use AI tooling effectively while understanding, reviewing and being able to defend the code you ship.

Required Qualifications

• 2-4+ years of professional experience in software engineering, data engineering or a related technical role.
• Experience with PySpark, Apache Iceberg, dbt or modern lakehouse technologies.
• Experience building internal Python packages, libraries or CLI tools.
• Experience with AWS, GCP or Azure.
• Strong Python skills, with experience writing clean, reusable and maintainable production code beyond standalone scripts.
• Strong SQL skills and hands‑on experience working with relational databases such as PostgreSQL, MySQL or similar.
• Experience building or supporting data pipelines and working with structured datasets.
• Good understanding of data modelling, data quality, failure handling and operational reliability.
• Experience working with production systems in a cloud or deployed environment.
• Strong debugging and problem-solving skills, with the ability to work independently and take ownership of technical tasks.
• Experience working within an engineering team through code reviews, documentation, tickets and technical communication.
• Comfortable collaborating with data scientists or researchers and working with analytical or data-intensive workflows.

Desirable Skills

• Experience with Docker, CI/CD pipelines and Terraform or other infrastructure-as-code tooling.
• Experience with Grafana or similar monitoring and observability platforms.
• Experience with workflow orchestration tools such as Airflow, Prefect or Dagster.
• Experience optimising systems or queries for large datasets.
• D familiarity with security best practices for application code, databases and data workflows.