Data Engineer, Expert (Snowflake)

Location: Hybrid in Oakland, California, with work from a remote office and an assigned location within the PG&E Service Territory based on business needs.

Salary: estimated placement range of $140,000–$190,000; reasonable Bay Area range of $140,000–$238,000.

Company

hirify.global operates in the energy delivery sector.

What you will do

• Design, build, and maintain scalable ELT/data pipelines with Snowflake, Airflow, Informatica, and AWS services.
• Develop a unified Snowflake Data Lakehouse across Bronze, Silver, and Gold layers for vegetation management, regulatory compliance, and analytics.
• Integrate structured, semi-structured, and unstructured data from Salesforce, SAP, SharePoint, ArcGIS, and remote sensing imagery.
• Enable machine learning feature pipelines and model input/output flows, including integrations with SageMaker or Foundry.
• Apply version control, CI/CD, unit testing, infrastructure-as-code, monitoring, data quality, lineage, and governance practices.
• Collaborate with data scientists, analysts, and business stakeholders; mentor junior engineers and contribute to architecture, reviews, and knowledge sharing.

Requirements

• BA/BS in computer science, Management Information Systems, or a related field, or equivalent experience.
• At least 7 years of experience with data engineering or ETL ecosystems, including Palantir Foundry, Spark, Informatica, SAP BODS, or OBIEE.
• Experience with multiple data engineering/ETL ecosystems and machine learning algorithm deployment.
• Ability to collaborate cross-functionally and communicate technical concepts to technical and non-technical audiences.

Nice to have

• Master’s degree in computer science, Management Information Systems, or a related field, or equivalent experience.
• Experience building scalable pipelines for structured, semi-structured, and unstructured data; Snowflake, Databricks, or AWS Redshift; Informatica or AWS Glue; and Apache Spark.
• Proficiency in SQL and Python, Scala, or Java.
• Experience with unit testing, TDD, CI/CD, Git, GitHub, Terraform, or CloudFormation.
• Experience with AWS services including S3, Lambda, Step Functions, Fargate, DynamoDB, SNS/SQS, and CloudWatch.
• Experience deploying and operationalizing machine learning models in production, using Power BI, Tableau, or Foundry, and working with ArcGIS, data catalogs, metadata, lineage, Informatica, or Collibra.

Culture & Benefits

• Hybrid work combining a remote office with an assigned PG&E Service Territory location.
• Eligibility for discretionary incentive compensation programs.
• Salary is determined by skills, education, licenses or certifications, experience, market value, location, collective bargaining agreements, and internal equity.