Junior Analytics Engineer

SewerAI Corporation•Walnut Creek, CA

1d•$90,000 - $110,000

About The Position

SewerAI is transforming underground infrastructure management through AI-powered inspection and risk analysis. Our platform helps contractors, engineering firms, and utilities unlock valuable insights from sewer inspection data—turning hours of manual video review into actionable intelligence in minutes. After doubling our customer base over the past year, we’re now entering an exciting phase of accelerated growth. We're hiring our second member of the Data team. You'll join a high-impact, fast-moving data function as a Junior Analytics Engineer, working directly under and mentored by our Senior Data Engineer. Our data team supports the entire company — Sales, RevOps, Finance, Customer Success, Marketing, and Product all depend on the warehouse, models, and dashboards we build. This is an ideal role for someone early in their analytics-engineering career who wants to grow quickly. You'll start by owning well-scoped, high-volume work — data models, dashboards, and analytical requests — and take on increasing complexity over time as you ramp. You'll get broad exposure to a modern data stack and direct mentorship from a senior engineer, with a clear path to grow your skills across modeling, pipelines, and warehouse engineering.

Requirements

1–3 years of production experience in an analytics engineering, data analyst, data engineering, or BI role.
Strong SQL skills — comfortable writing, reading, and debugging non-trivial queries (joins, aggregations, window functions, CTEs).
Working proficiency in Python for data manipulation and scripting.
Familiarity with a cloud data warehouse (e.g., ClickHouse, Snowflake, BigQuery, Redshift, or similar) and core data-modeling concepts.
Experience building dashboards or reports in a BI / analytics tool (e.g., Hex, Looker, Tableau, Power BI, Metabase, or similar).
Solid data-quality instincts: able to sanity-check results, spot anomalies, and validate numbers before they reach stakeholders.
Clear written and verbal communication, with the ability to translate between technical detail and business questions for non-technical audiences.
A self-starter who can manage a queue of incoming requests, prioritize sensibly, and ask good clarifying questions.

Nice To Haves

Hands-on experience with dbt (or a similar transformation/modeling framework).
Experience with ClickHouse specifically, or with materialized views and warehouse performance tuning.
Experience building or maintaining ETL/ELT pipelines and integrating third-party APIs (e.g., Salesforce, QuickBooks, Mixpanel, Google Analytics/Ads, or similar SaaS sources).
Experience with Agentic Engineering workflows.
Familiarity with Hex as a notebook/BI/semantic-layer platform.
Exposure to data replication / CDC concepts (e.g., Postgres logical replication, ClickPipes, peerDB) and scheduled jobs / CRON-based workflows.
Experience supporting RevOps, Finance, or GTM analytics (ARR/MRR, billing, pipeline, usage, or CAC reporting).
Basic familiarity with version control (Git) and cloud infrastructure (AWS — S3, IAM).
Comfort working with semantic layers and self-serve / LLM-assisted analytics tooling.

Responsibilities

Build and maintain data models in our semantic/modeling layer (dbt and a SQL-based semantic model) so the rest of the company can self-serve trustworthy analytics.
Create, update, and troubleshoot business-facing dashboards and reports for stakeholders across the company.
Respond to ad-hoc data requests — pulling, validating, and clearly communicating data to non-technical teammates.
Help maintain ingestion and data-refresh pipelines from third-party sources (CRM, finance, product, and marketing platforms), including routine connection and credential upkeep.
Investigate and resolve data-quality issues such as missing fields, incorrect values, and failed scheduled jobs.
Support stakeholders directly through team office hours and a data support channel, helping non-technical users get answers from our tools.
Document models, metrics, and common workflows so definitions stay consistent across the company.
Partner closely with the Senior Data Engineer, who will review your work and progressively hand off more complex projects as you grow.