Senior Data Engineer (US)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-09-29). Last seen at its source 1h ago.
We have tracked this listing since 29 Sep 2026 (2 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
Remote - US
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$155k–170k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
lever employer's own board first seen 2d ago · last seen 1h ago
The listing
The Senior Data Engineer will design and build reliable data solutions that translate complex product and business logic into scalable, well-tested data models and pipelines. This role requires deep expertise in SQL, query acceleration, and applying GenAI to both engineering workflows and data/analytics interfaces. They will partner across engineering, analytics, and business teams, contribute to shared codebases, improve data quality and observability, and help evolve the data architecture.
Responsibilities
-
Design, build, and maintain scalable data pipelines, warehouse models, and analytics solutions, balancing data quality, business value, and speed.
-
Build and maintain natural language interfaces to data and analytics, applying GenAI/LLM techniques to make data more accessible across the business.
-
Use GenAI coding tools and practices in daily development to improve code quality, testing, and delivery speed.
-
Continuously evaluate new technologies that could improve and scale the team's data platform and technology stack.
-
Establish and follow standards for SQL development, data modeling, testing, documentation, code reviews, and production support.
-
Support production data pipelines through on-call rotation and incident response, partnering with engineering, analytics, and business teams.
-
Document and maintain expertise in the technology stack and product domain, translating business needs into technical solutions with product management.
Minimum Qualifications
-
Bachelor's degree in Computer Science or related field, or equivalent professional experience.
-
8+ years building reliable, high-performance, large-scale distributed systems, with an emphasis on streaming and data pipelines.
-
Experience working with and maintaining multi-tenant SaaS experiences.
-
Experience building natural language interfaces over data warehouses, including applying GenAI/LLM techniques to data and analytics.
-
Enterprise-level experience with at least one large-scale analytical data warehouse or query engine: StarRocks, Amazon Redshift, Snowflake, Databricks, or Trino.
-
Expertise writing, optimizing, and analyzing SQL.
-
Hands-on experience building and operating distributed data platforms on AWS or GCP.
-
Hands-on experience with streaming platforms such as Kafka and Spark.
-
Experience scaling data modeling and warehousing.
-
Proficiency in python.
Preferred Qualifications
-
Experience with Cube or other semantic layers.
-
Experience with scheduling tools such as Airflow.
-
Familiarity with the BI tool Metabase.
-
Proficiency in Ruby on Rails, React, or other adjacent languages.