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# Data Engineer

- **Company:** INCEED
- **Location:** Denver, CO, United States
- **Experience:** Expert
- **Salary:** $135,200.0 - $176,800.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Microsoft Azure, BigQuery, Cloud Computing, Databases, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), PostgreSQL, NumPy, Operational Data Store, SQL Server Integration Services, Data Streaming, Sql Optimization, Snowflake, Palantir Foundry, Pandas, Build Management, Apache Flink, Apache Kafka, Stream Analytics, Data Pipelines, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.adzuna.com/details/5927270252

## About the Role

* 8+ years of relevant data engineering experience
 * Strong experience with large oil and gas datasets
 * Advanced SQL skills with complex querying and transformations
 * Proficiency in Python and data libraries like pandas and numpy
 * Hands-on cloud experience in Azure, AWS, or GCP
 * Experience with modern data platforms like Snowflake, Databricks, or BigQuery
 * Background building ETL or ELT workflows
 * Ability to work independently in ambiguous environments

Nice to Have Skills & Experience:

 * Experience with Kafka, Flink, or Azure Event Hubs
 * Familiarity with dbt, Airflow, Fivetran, Matillion, or SSIS
 * Experience with Denodo, Trino, or Starburst
 * Knowledge of SQL Server or PostgreSQL
 * Exposure to Palantir Foundry
 * Experience with seismic, SCADA, or 3D geo models
 * Prior work in exploration or geoscience-focused teams

## Description

* Design and build scalable data pipelines and architectures
 * Integrate data from APIs, databases, flat files, and streaming sources
 * Support near real-time analytics and operational data workflows
 * Collaborate with stakeholders, engineers, and data teams
 * Develop automation and BI solutions for business users
 * Ensure data quality, consistency, and reliability across systems
 * Contribute best practices for data engineering and process improvement
 * Evaluate emerging tools and technologies for future use