Data Solutions Engineer

PowerSecure, Inc.

Data Engineer designing and building data pipelines on PowerSecure’s Azure data platform. Collaborating with BI Developers and Data Architects to deliver high-quality data solutions.

Posted 4/15/2026full-timeRemote • California • 🇺🇸 United StatesJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

AzureCloudPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Design, implement, and support end‑to‑end ELT pipelines (ingest → transform → publish) in Databricks/ADF
Implement data quality checks (DLT expectations, unit tests) with alerting and remediation runbooks
Build curated, analytics‑ready Delta tables using dimensional modeling for consumption by BI Developers
Implement CDC and deletion‑flag patterns; manage schema drift and partitioning/Z‑Ordering strategies
Operationalize jobs with monitoring, logging, alerting; participate in an on‑call rotation as needed
Partner with the Data Architect to align designs with standards for governance, security, and cost efficiency
Document pipelines, data contracts, and SLAs; continuously improve performance and reliability

Requirements

What you’ll need

2+ years of hands‑on data engineering (or comparable software engineering with significant data work)
2+ years building pipelines on Azure and Databricks (or equivalent cloud + Spark)
Strong SQL (analytical queries, window functions), PySpark/Spark SQL, and data modeling fundamentals
Bachelor’s degree in MIS, Computer Science, Engineering, or equivalent experience
Proficiency with SQL and Python (PySpark), including performance tuning on large datasets
Experience with Azure Databricks, Delta Lake, Delta Live Tables (DLT), Azure Data Factory (or Fabric Data Pipelines), ADLS Gen2, and Azure DevOps/Git for CI/CD
Working knowledge of Unity Catalog and/or Microsoft Purview for governance, lineage, and security
Familiarity with data ingestion patterns (files, APIs, JDBC), schema evolution, CDC, and deletion detection patterns
Understanding of dimensional modeling to produce analytics‑ready datasets for Power BI
Exposure to orchestration/monitoring, cost optimization, alerting, and runbook‑driven operations
Data pipeline design (batch & streaming), DLT expectations for data quality, and robust error handling
Source control, branching strategies, and CI/CD for data assets (notebooks, jobs, workflows)
Practical understanding of privacy, security, and RBAC in cloud data platforms
Excellent communication, documentation, and cross‑functional collaboration skills
Analytical mindset; bias toward automation and measurable reliability

Benefits

Comp & perks

Medical, dental, vision and life insurance coverage
Competitive pay and a matching 401 (k) plan
Vacation, Company Holidays, Paid Time Off (PTO- personal and sick days)
Flexible spending accounts/Health savings account
Wellness Incentive Programs
Employee Referral Program
Tuition Reimbursement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringSQLPySparkdata modelingperformance tuningdata pipeline designdimensional modelingdata quality checksCDCalerting

Soft Skills

communicationdocumentationcross-functional collaborationanalytical mindsetautomationmeasurable reliability

Certifications

Bachelor's degree in MISBachelor's degree in Computer ScienceBachelor's degree in Engineering