Junior Analytics Engineer

Summary

SewerAI is transforming underground infrastructure management through AI-powered inspection and risk analysis. They are seeking a Junior Analytics Engineer to join their data team, where the individual will work on data models, dashboards, and analytical requests while receiving mentorship from a Senior Data Engineer.

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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

Benefits

• Equity opportunities available
• Medical, Dental, Vision, Basic Life, 401(k), and more
• Unlimited PTO
• Tools and resources to support success