Senior Data Analytics Engineer
Liberty Mutual Insurance · Seattle, WA
$106,000–$197,000
Jul 6, 2026
Seattle, WA
Jul 20, 2026
What this job asks for AI summary
Senior level · 5+ years · National · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $142,568 (middle half $111,775–$173,013).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
Location is not specified in the posting; Liberty Mutual is headquartered in Boston, MA, but the role notes 'in-office requirements dependent upon candidate location,' suggesting a distributed/national hire. No CBSA was assigned.
The degree requirement is ambiguous: a Bachelor's is listed as 'preferred' and a Master's as 'strongly preferred' — neither is a hard gate, so the degree requirement is set to None.
AWS is listed alongside Snowflake as a cloud platform example ('such as Snowflake and AWS'), placing it in the required qualifications block; alternatives reflect other major cloud platforms a hiring manager would accept.
dbt and Databricks are explicitly called out as 'a plus' in the candidate profile section, so both are marked preferred, with Databricks listed as an alternative to dbt since the posting treats them interchangeably as bonus credentials.
The Qualifications section also references NoSQL, Java, Perl, Shell scripting, Hadoop, and BI tools (5-7+ years each), but these appear in a broad, catch-all list typical of a legacy job template and are not reinforced elsewhere in the posting as active requirements for this role. They are omitted to avoid overstating hard gates.
The role sits at the boundary between data/pipeline engineering (15-1243) and data science/analytics (15-2051); the primary emphasis on ETL pipelines, data modeling, and Snowflake/SQL infrastructure tips it toward 15-1243, but the analytics and insights responsibilities make 15-2051 a credible runner-up.
Read the full posting
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