Data Engineer

Siri InfoSolutions Inc; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Siri InfoSolutions Inc in Glendale, CA is seeking a Data Engineer for a 12-month contract with extensions. The role is onsite with an initial requirement of 2 days per week on site, potentially increasing to 4 days.

You will build and debug data pipelines, support testing use cases, and contribute to production code under peer review, with a strong emphasis on code quality and reliability.

Qualifications

• Must have Spark experience.
• Must have SQL experience.
• Onsite 2 days per week with potential up to 4 days.

Responsibilities

• Work directly on data pipelines
• Debug and resolve pipeline issues
• Support testing use cases
• Contribute to production code with peer review oversight
• Focus on code quality and reliability

Skills

Spark experience

SQL experience

Tools

Databricks

AWS

Job description

Data Engiee

Description: Title: Data Engineer

Contract Duration: 12 months + extensions

Location: Glendale,

Onsite Requirement

Current requirement: 2 days per week onsite

Potential future increase to up to 4 days, but not confirmed

Must work onsite hybrid starting week 1 (2 weeks max from the time of offer acceptance)

Zero exceptions will be made, as this is corporate policy - no delayed remote start, no remote work

2 days a week onsite, must be flexible up to 4 days a week onsite

Core Responsibilities

The candidate will be expected to:

• Work directly on data pipelines
• Debug and resolve pipeline issues
• Support testing use cases
• Contribute to production code with peer review oversight
• Focus on code quality and reliability

Must-Have Skills

The must-have requirements have been refined:

• Spark experience (must-have)
• SQL experience (must-have)

Preferred / secondary:

• Databricks (preferred, not required)
• AWS (preferred cloud platform)

Cloud & Technical Expectations

• AWS is the preferred cloud environment
• Multi-cloud experience is acceptable at the junior level, but less scrutiny is applied compared to senior roles
• Less emphasis on architectural reasoning for junior candidates
• Focus is on practical, hands-on experience rather than theoretical decision-making

Experience in mid-sized companies

• More hands-on pipeline troubleshooting and maintenance
• Ability to identify and resolve pipeline issues using basic to mid-level methods ("ABC methods")
• Less emphasis on advanced architecture or large-scale system design

The role is now more execution-focused, with the expectation that candidates will:

• Be overseen and mentored by senior team members
• Participate in peer code reviews focused on quality and testing
• Grow into the role over time

The hiring manager clarified:

• The role is purely data engineering
• Analytics is not a core responsibility
• The team's function is to provide data for business teams to analyze, not perform analytics themselves

Marketing Data Exposure

• Marketing data experience is optional / nice-to-have
• The environment is small-scale (approximately 5 6 people historically)
• Not a core requirement for the role

Candidate Profile

Ideal candidates (3-year level) are expected to be:

• Early in their career / recently in the workforce
• Highly adaptable and fast learners
• Strongly hands-on and execution-focused
• Comfortable troubleshooting real production issues
• Less focused on organizational or architectural decision-making

They are expected to:

• Adapt quickly to new tools
• Focus on solving problems rather than debating platform decisions

Technical Assessment

A technical assessment is being considered.

Key preferences:

• Should evaluate real-world problem-solving ability
• Should measure candidate approach and thinking, not just correctness
• Should avoid being purely syntax-based or "right/wrong" focused