Data Engineer – Time-Series & Alarm Analytics

Apex Systems; Spring (TX); On-site; USD 110,000 - 150,000; Full time

Job summary

Everforth Apex is seeking a Data Engineer to develop analytics and dashboards, using Databricks and Power BI to integrate, clean, transform, and analyze time-series data from alarm and process historian sources. The role focuses on identifying trends, tracking corrective actions, and communicating findings to stakeholders.

You will build and maintain dashboards, validate data quality, and translate insights into actionable recommendations for alarm performance and reliability improvements onsite

Qualifications

• Experience with Databricks for data integration, transformation, querying, and analysis.
• Experience extracting data from Databricks, Snowflake, or process historians.
• Strong Power BI dashboarding and data modeling skills; SQL and Python proficiency.

Responsibilities

• Use Databricks to integrate, clean, transform, and analyze data from alarm systems, process historians, maintenance systems, and instrument databases.
• Develop and maintain Power BI dashboards for alarm performance, alarm floods, bad actors, instrument reliability, trends, and corrective-action tracking.
• Validate data quality and document data sources, assumptions, business rules, and analytical methods.
• Analyze high-volume, time-series data.
• Translate complex data into findings, recommendations, and prioritized corrective actions.

Skills

Databricks

SQL

Python

Data analysis

Time-series analysis

Tools

Power BI

Snowflake

DCS/SCADA

Process historians

Databricks

Job description

Everforth Apex is seeking a Data Engineer to develop analytics and dashboards, using Databricks and Power BI to integrate, clean, transform, and analyze time-series data from alarm and process historian sources. The role focuses on identifying trends, tracking corrective actions, and communicating findings to stakeholders.

You will build and maintain dashboards, validate data quality, and translate insights into actionable recommendations for alarm performance and reliability improvements onsite