Data Engineer – Oil & Gas · Skills Database

About the role

Client: oil and gas company (upstream operator, Houston HQ) · Location: remote, LATAM, Houston business hours · Level: senior · Engagement: full-time contractor You will build the pipelines that move well, production and sensor data from the field into a cloud lakehouse used by engineers and analysts. What you will do Ingest time-series data from SCADA and historians (OSIsoft PI, OPC UA) alongside ERP and production accounting sources Build batch and streaming pipelines on Databricks or Snowflake with Spark, Kafka and Airflow Model data in a medallion architecture for production, drilling and maintenance analytics Enforce data quality, lineage and access controls Work with reservoir and production engineers to turn their questions into datasets Optimize pipeline cost and performance What you bring 5+ years in data engineering Strong SQL and Python, plus Spark in production Experience on Azure or AWS data stacks Orchestration with Airflow or similar, and dbt for transformations Experience with high-volume time-series or IoT data Advanced English Nice to have Oil and gas domain knowledge (WITSML, PPDM, OSDU) PI System integration experience Spanish or Portuguese for work with LATAM operations Originally posted on Himalayas

Skills mentioned in the listing

PythonSQLAWSAzureSparkDatabricksSnowflakeData engineeringERPSCADA configuration

Recognised skills are extracted from the supplied description using canonical names and aliases. They are mentions, not verified essential requirements. Check the source advert for the employer’s full requirements and location restrictions.

Why these skills appear

Python · mentioned
and performance What you bring 5+ years in data engineering Strong SQL and Python, plus Spark in production Experience on Azure or AWS data stacks Orchestration with Airflow or similar, and dbt for transformatio

SQL · mentioned
ne cost and performance What you bring 5+ years in data engineering Strong SQL and Python, plus Spark in production Experience on Azure or AWS data stacks Orchestration with Airflow or similar, and dbt for trans

AWS · requirement-context
ring Strong SQL and Python, plus Spark in production Experience on Azure or AWS data stacks Orchestration with Airflow or similar, and dbt for transformations Experience with high-volume time-series or IoT data

Azure · requirement-context
a engineering Strong SQL and Python, plus Spark in production Experience on Azure or AWS data stacks Orchestration with Airflow or similar, and dbt for transformations Experience with high-volume time-series or I

Spark · mentioned
g sources Build batch and streaming pipelines on Databricks or Snowflake with Spark, Kafka and Airflow Model data in a medallion architecture for production, drilling and maintenance analytics Enforce data quality,

Databricks · mentioned
ERP and production accounting sources Build batch and streaming pipelines on Databricks or Snowflake with Spark, Kafka and Airflow Model data in a medallion architecture for production, drilling and maintenance anal

Snowflake · mentioned
ction accounting sources Build batch and streaming pipelines on Databricks or Snowflake with Spark, Kafka and Airflow Model data in a medallion architecture for production, drilling and maintenance analytics Enforc

Data engineering · mentioned
datasets Optimize pipeline cost and performance What you bring 5+ years in data engineering Strong SQL and Python, plus Spark in production Experience on Azure or AWS data stacks Orchestration with Airflow or

ERP · mentioned
ngest time-series data from SCADA and historians (OSIsoft PI, OPC UA) alongside ERP and production accounting sources Build batch and streaming pipelines on Databricks or Snowflake with Spark, Kafka and Airflow Model

SCADA configuration · mentioned
used by engineers and analysts. What you will do Ingest time-series data from SCADA and historians (OSIsoft PI, OPC UA) alongside ERP and production accounting sources Build batch and streaming pipelines on Databrick