Job Title:- Senior Data Engineer Databricks / SQL / Snowflake
Location:- Spring Texas (100% On-Site)
Job Type:- Long Term Contract - Expected 2+ year engagement
Responsibilities:
Client is seeking an experienced Data Engineer to join a small, high-impact team building a new Authorization for Expenditure (AFE) data product supporting Project Nexus, an upstream data harmonization initiative.
The engineer will play a key role in designing and developing a data solution that connects multiple enterprise datasets to provide a holistic, start-to-finish view of major capital project spending.
The platform will enable stakeholders to compare:
- Original budgeted/projected expenditure
- Actual expenditure
- Variances between planned and actual spend
- Business and operational factors responsible for those variances
The ideal candidate will have very strong hands-on experience with Databricks, Databricks Notebooks, and SQL. Experience with Snowflake is highly preferred because the semantic/data consumption layer will reside in Snowflake.
There is also an AI component within the initiative, so exposure to AI-enabled data engineering, Databricks AI capabilities, or AI-assisted development is beneficial.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks.
- Perform hands-on development using Databricks Notebooks.
- Write complex, optimized SQL queries for data transformation, analysis, and integration.
- Integrate and harmonize data from multiple enterprise datasets and source systems.
- Build data models supporting the AFE / capital expenditure lifecycle.
- Develop datasets that enable comparison of budgeted spend versus actual spend.
- Identify and expose drivers contributing to expenditure variances.
- Work closely with a small engineering/product team supporting the broader Project Nexus upstream harmonization initiative.
- Support integration between Databricks and Snowflake.
- Contribute to the creation and maintenance of the Snowflake semantic layer used by downstream consumers.
- Ensure data quality, reliability, scalability, and performance.
- Participate in testing, troubleshooting, optimization, and production deployment.
- Support the data product after development transitions into production.
- Eventually transition with the product into a longer-term production support and enhancement organization.
- Explore and leverage relevant AI capabilities within Databricks or the data engineering workflow where appropriate.
Required Qualifications
- Strong professional experience as a Data Engineer.
- Advanced hands-on experience with Databricks.
- Strong experience developing solutions using Databricks Notebooks.
- Advanced SQL skills.
- Experience building and maintaining enterprise-scale data pipelines.
- Strong experience integrating data from multiple heterogeneous data sources.
- Experience with data transformation, data modeling, and data quality.
- Ability to troubleshoot and optimize complex data workloads.
- Strong communication skills and ability to work within a small, collaborative engineering team.
- Ability to work onsite in Spring, Texas 5 days per week.
Highly Preferred
- Hands-on Snowflake experience.
- Experience integrating Databricks with Snowflake.
- Experience building or working with semantic/data consumption layers.
- Experience with financial, budgeting, expenditure, or capital project data.
- Experience within Oil & Gas / Energy / Upstream environments.
- Experience working with enterprise-scale data platforms.
- Exposure to AI / Generative AI / ML-enabled data engineering.
- Experience using AI functionality available through Databricks.
- Experience supporting production data products after initial development.
Project Lifecycle
The initial development phase is expected to run for approximately
one year.
Once the AFE data product moves into production, the Data Engineer is expected to transition with the solution into the organization responsible for its ongoing
support, maintenance, and enhancements.
Because of this lifecycle, the opportunity is expected to last approximately
two years or potentially longer.
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