DataSMBEnterprise

Analytics Engineer

[Company Name] is hiring an Analytics Engineer to bridge the gap between raw data and actionable business insights. You will design, build, and maintain the data models and transformations that power dashboards, reports, and self-serve analytics across the organization. This role sits at the intersection of data engineering and data analysis, and is critical to ensuring our teams make decisions based on trusted, well-documented data.

Download DOCXDownload PDFUse in Talantrix

Key Responsibilities

  • Design and maintain dimensional data models in the analytics warehouse using dbt or similar tools
  • Build and optimize SQL-based data transformations that are reliable, tested, and well-documented
  • Partner with business stakeholders to understand data needs and translate them into reusable data models
  • Create and maintain dashboards and reports in BI tools such as Looker, Tableau, or Metabase
  • Define and enforce data quality standards including tests, freshness checks, and anomaly detection
  • Document data models, metrics definitions, and lineage to improve data literacy across the company
  • Collaborate with data engineers on pipeline architecture and with analysts on metric definitions

Required Skills & Experience

  • 3+ years of experience working with data in an analytics or data engineering role
  • Expert-level SQL skills including window functions, CTEs, and query performance optimization
  • Hands-on experience with dbt (data build tool) for data modeling and transformation
  • Proficiency with at least one modern cloud data warehouse (Snowflake, BigQuery, Redshift, or Databricks)
  • Experience building dashboards and reports in a BI tool (Looker, Tableau, Power BI, or Metabase)
  • Strong understanding of dimensional modeling (star schema, slowly changing dimensions)
  • Excellent communication skills and ability to work closely with non-technical stakeholders

Nice-to-Have

  • Experience with Python for data scripting or pipeline orchestration
  • Familiarity with data orchestration tools like Airflow, Dagster, or Prefect
  • Knowledge of data governance and cataloging tools (Atlan, DataHub, Monte Carlo)
  • Experience with version control (Git) and CI/CD for analytics code
  • Background in a business domain like finance, marketing, or product analytics

Tech Stack

dbtSnowflakeBigQueryLookerTableauSQLAirflowGitPythonFivetran

What We Offer

  • Competitive salary and equity package
  • Flexible remote or hybrid work arrangement
  • Health, dental, and vision insurance
  • Annual learning and development budget
  • Generous PTO policy

Interview Process

  1. 1Recruiter phone screen (30 min)
  2. 2Hiring manager conversation covering experience and role expectations (45 min)
  3. 3Technical assessment: SQL modeling exercise and data modeling case study (60 min)
  4. 4Cross-functional interview with a business stakeholder to assess communication and collaboration (30 min)
  5. 5Final interview with team lead or director

Hiring for this role? You might also need:

Interview Scorecards

Bar Raiser

Bar Raiser — Cross-Functional

Independent bar-raiser assessment ensuring the candidate raises the team's overall bar.

Culture & Values

Culture & Values Interview

Behavioral interview scorecard covering collaboration, ownership, and growth mindset.

Hiring Manager

Hiring Manager Final Round

Final evaluation by hiring manager: team fit, role alignment, and leadership potential.

Phone Screen

Recruiter Phone Screen (Universal)

General-purpose recruiter screen covering motivation, experience fit, and logistics.

Email Templates

Sourcing

Cold Outreach — Passive Developer

A personalized first-touch email to engage passive developers who aren't actively job hunting.

Interview Scheduling

Technical Interview Invitation

An email inviting a candidate to a technical interview with details on format, duration, and how to prepare.

Decision & Offer

Offer Letter Email

A congratulatory email extending a formal job offer with key terms and the attached offer letter.

Related Templates

Data

Data Engineer

Build and maintain data pipelines, warehouses, and ETL processes at scale.

Data

Data Analyst

Turn raw data into actionable insights through SQL, visualization, and statistical analysis.

Data

Data Scientist

Build predictive models and use statistical methods to solve complex business problems.

Back to all templates