The ideal candidate will have a strong background in data engineering, data modelling, and cloud-based data platforms with a clear understanding of upstream/downstream data structures, exploration data, and production workflows.

This role involves working closely with stakeholders, business analysts, and domain experts to build a reliable, scalable, and secure data infrastructure that supports analytics, reporting, and AI/ML solutions.

Key Responsibilities :

- Design, develop, and maintain data ingestion, transformation, and orchestration pipelines using technologies like PySpark, SQL, Databricks, and Airflow.

- Integrate data from various sources including SCADA, seismic systems, IoT sensors, drilling logs, and ERP systems.

- Perform data quality checks, data gap analysis, and resolve data inconsistencies across systems.

- Collaborate with stakeholders to manage master data mapping and align it with transactional data (e., well data, asset data).

- Work on data modeling for time-series data, production volumes, well logs, and reservoir data.

- Implement and optimize Delta Lake and data lake architectures on Azure or AWS platforms.

- Partner with data scientists and business teams to provision cleansed, validated, and transformed data for analytics use cases.

- Prioritize stakeholder requests using structured frameworks (e., MoSCoW, RICE) and ensure delivery based on business impact.

- Create visual prototypes or dashboards using Power BI/Tableau/Looker when specifications are vague and iterate based on feedback.

- Handle stakeholder conflicts with professionalism and use data-backed reasoning to arrive at resolutions.

Must-Have Skills :

- Strong programming skills in Python, SQL, and PySpark.

- Proficiency with Databricks, Delta Lake, and data lakehouse concepts.

- Experience working with cloud platforms: Azure Data Factory / AWS Glue / EMR.

- Data modelling experience for Oil & Gas data types (wells, assets, production logs, seismic data).

- Familiarity with data quality frameworks and master data management (MDM).

- Version control (Git), CI/CD for data pipelines.

- Excellent communication skills and stakeholder management.

Good-to-Have Skills :

- Experience with Terraform or other Infrastructure-as-Code (IaC) tools.

- Exposure to Palantir Foundry, especially for large-scale E&P data integration.

- Knowledge of industry standards such as PPDM, WITSML.

- Understanding of analytics, ML pipelines, or time-series forecasting.

- Familiarity with data governance, access control, and compliance.

Domain Experience :

- Minimum 2+ years in the Oil & Gas domain, preferably with upstream or midstream exposure.

- Understanding of business processes like exploration & production (E&P), reservoir management, drilling operations, asset lifecycle, and real-time monitoring.

Education :

- Bachelors or Masters in Computer Science, Data Engineering, Petroleum Engineering, or a related field.