Data Engineer

Join a dynamic team in Spring, Texas as a Data Engineer, where you’ll drive impactful analytics and visualization to enhance alarm system performance and reliability. Utilize advanced tools such as Databricks and Power BI to manage high-volume, time-series data and deliver actionable insights. This full-time, onsite position offers hands-on experience with cutting-edge technologies in a collaborative, growth-focused environment., Integrate, clean, and transform data from alarm systems, process historians, maintenance systems, and instrument databases using Databricks

• Develop and maintain Power BI dashboards for alarm performance, alarm floods, bad actors, instrument reliability, trend analysis, and corrective-action tracking
• Validate data quality, document data sources, business rules, and analytical methods
• Analyze large-scale, complex time-series datasets to identify trends and root causes
• Translate complex data findings into clear recommendations and prioritized corrective actions

Proficiency in Databricks for data integration, transformation, querying, and analysis

• Proven experience in extracting and analyzing data from Databricks, Snowflake, data historians, and similar sources
• Advanced skills in Power BI dashboard creation and data modeling
• Strong SQL and Python coding abilities
• Experience with data extraction from DCS, SCADA, and process historians

Preferred Skills

• Familiarity with additional analytics platforms or data engineering tools
• Demonstrated experience in process industry data environments
• Strong documentation and reporting skills, Top 3 skill sets/technologies required for qualification:1): Data analysis with extraction of data from Databricks Snowflakes data historian or any other sources2): Dashboard creation and modelling (Power BI)3): SQL Python coding

Opportunity to work onsite with industry-leading technologies and systems

• Collaborative work environment with a focus on innovation and professional growth
• Exposure to high-impact projects critical to operational efficiency and safety