SRE Data Engineer

As an SRE Data Engineer, you will help build a new enterprise data environment for a global media and entertainment organization, starting with ServiceNow data and expanding into analytics, automation, and future AI capabilities. Stand8 provides end to end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India.

Stand8 provides end to end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India.

As an SRE Data Engineer, you will help build a new enterprise data environment for a global media and entertainment organization, starting with ServiceNow data and expanding into analytics, automation, and future AI capabilities. You will build the pipelines, models, integrations, and warehouse components that make operational information accessible across the business and support enterprise reporting. This role offers an opportunity to contribute early to technology decisions, work alongside engineering, platform, and business teams, and bring new capabilities into production as adoption grows. The ideal candidate has a strong foundation in Python and SQL and is excited to work with modern enterprise cloud environments, including AWS, Snowflake, and ServiceNow.

Location & Work Type

Location: Must be located within commuting distance (50 miles) of Los Angeles, CA; Miami, FL; New York, NY; or Stamford, CT. Occasional onsite attendance to one of these locations will be required.

Work Type: Hybrid

Key Responsibilities

• Help establish the data warehouse framework, schemas, and data models needed to support enterprise operational reporting and automation.
• Develop, maintain, and optimize production-quality Python and SQL code integrations for data ingestion, transformation, validation, and processing.
• Build extract, transform, and load (ETL) pipelines that convert raw source data into structured reporting tables and reusable datasets.
• Integrate data primarily from ServiceNow into an external data platform, coordinating with source-system and platform teams.
• Support and improve the current data flow through Amazon Simple Storage Service (Amazon S3) and Snowflake.
• Help evaluate platform options, including Snowflake and Amazon Relational Database Service (Amazon RDS), based on business needs and technical constraints.
• Configure and use existing application programming interfaces (APIs) and integration methods to support reliable data movement.
• Create and enhance reporting views, add data elements, and onboard new datasets as stakeholder requirements evolve.
• Implement data quality checks, testing, monitoring, and troubleshooting processes to maintain accurate and dependable data.
• Investigate production issues and improve database performance, pipeline reliability, scalability, and operational efficiency.
• Apply data governance, security, access control, and metadata management practices in collaboration with enterprise teams.
• Collaborate with product, engineering, operations, security, architecture, and business stakeholders to translate requirements into working solutions.
• Contribute to code reviews, reusable engineering patterns, deployment automation, and technical documentation.
• Prepare accessible datasets for visualization and future AI-enabled or agentic workflows, and develop prototypes when needed to validate approaches.

Qualifications

Required:

• Approximately 3-5 years of experience building and supporting data engineering, database, analytics, or integration solutions.
• Strong hands-on Python and Structured Query Language (SQL) skills, including writing, troubleshooting, and optimizing production code.
• Experience designing, building, and maintaining relational databases or data warehouses, including schemas, tables, views, and data models.
• Experience developing ETL pipelines and transforming raw data into reliable datasets for reporting or downstream applications.
• Ability to work with existing APIs, source-system integrations, and data ingestion processes.
• Understanding of data quality, validation, governance, security, and metadata management.
• Experience testing, monitoring, troubleshooting, and supporting production data solutions.
• Familiarity with version control, automated deployment, and collaborative engineering practices.
• Strong analytical and critical-thinking skills, with the ability to evaluate options and recommend practical solutions.
• Excellent communication and collaboration skills, including the ability to discuss requirements and technical decisions with business and engineering stakeholders.
• Ability to learn new platforms quickly and apply established database and programming skills across different technologies.

Preferred (Optional):

• Experience with Snowflake, Databricks, or comparable cloud data warehouse or lakehouse platforms.