Data engineer /Architect - SigmaFlow SME San Diego

Data engineer /Architect - SigmaFlow SME  San Diego

the role is based out of San Diego Remote need l

.Candidates in San Diego are preferred, however, the role is remote, but the candidates MUST work in PST Hours.

Location - San Diego, CA - NEED LOCAL CANDIDATES WITH THE DL.

Need LinkedIn with the full location & profile picture.

Job Summary

We are seeking a highly skilled SigmaFlow Subject Matter Expert (SME) with experience in database technologies and to support, optimize, and extend SigmaFlow-based data pipelines and workflows. This role will serve as the technical authority for SigmaFlow implementations, ensuring reliable data ingestion, transformation, analytics, and integration with enterprise systems.

The ideal candidate combines hands-on engineering skills with architectural insight, and can partner effectively with data engineers, platform teams, and business stakeholders to deliver scalable, performant, and secure data solutions.

Key Responsibilities

SigmaFlow Platform Ownership

•    Act as the primary technical authority for SigmaFlow design, configuration, and operational best practices

•    Design, implement, and maintain SigmaFlow workflows for batch and near-real-time data processing

•    Optimize existing SigmaFlow pipelines for performance, reliability, and scalability

•    Troubleshoot and resolve complex workflow failures, data quality issues, and performance bottlenecks Database & Data Engineering

•    Design and maintain integrations between SigmaFlow and relational and non-relational databases (e.g., Oracle, PostgreSQL, SQL Server, MySQL, Snowflake, or similar)

•    Develop efficient SQL queries, stored procedures, and data models to support analytics and downstream applications

•    Ensure data integrity, lineage, and consistency across multiple data sources

•    Support large-volume data ingestion, transformation, and archival strategies Integration & Architecture

•    Collaborate with enterprise architects to design end-to-end data flow architectures

•    Integrate SigmaFlow with upstream and downstream systems such as OMS, ADMS, AMI, GIS, and enterprise data lakes (where applicable)

•    Support CI/CD pipelines for SigmaFlow and Python-based deployments

•    Ensure solutions align with security, compliance, and governance standards Operations & Support

•    Provide Tier 3 / SME-level support for production incidents and platform issues

•    Participate in root cause analysis (RCA) and implement long-term corrective actions

•    Create operational runbooks, standards, and technical documentation

•    Mentor engineers and analysts on SigmaFlow, Python, and database best practices Required Qualifications

Technical Skills

•    5+ years of experience in data engineering, workflow orchestration, or analytics platforms

•    Demonstrated hands-on expertise with SigmaFlow (design, configuration, troubleshooting)

•    Some understanding of Python for data processing, automation, and integrations

•    Advanced proficiency in SQL and relational database design

•    Experience working with large datasets and high-availability data platforms Platform & Tooling

•    Experience with Linux-based environments

•    Familiarity with version control systems (Git)

•    Experience with job scheduling, workflow orchestration, or ETL tools

•    Understanding of monitoring, logging, and alerting practices Preferred Qualifications

•    Experience in utility, energy, grid operations, or critical infrastructure environments

•    Familiarity with real-time or near-real-time data processing systems

•    Experience integrating with cloud data platforms or hybrid environments

•    Knowledge of data governance, metadata management, and compliance requirements

•    Exposure to containerization or DevOps practices Soft Skills & Competencies

•    Ability to operate as a trusted technical advisor and SME

•    Strong analytical and problem-solving skills

•    Excellent communication skills—able to explain complex technical concepts to non-technical stakeholders

•    Self-directed, detail-oriented, and comfortable working in mission-critical environments What Success Looks Like in This Role

•    SigmaFlow workflows are stable, performant, and well-documented

•    Data pipelines are reliable, scalable, and easy to support

•    Python automation reduces manual effort and improves operational efficiency