Senior Analytics Engineer

Astrodata; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Remote work with annual team offsite

Great health coverage (US)

401k with employer matching

Job summary

Astrodata is seeking a Senior Analytics Engineer to design and implement robust data solutions for ingestion, transformation, orchestration, and downstream delivery across diverse client environments.

You will architect a flexible semantic layer, lead ETL/ELT frameworks, and champion data quality with tests, contracts, and observability. This role collaborates with analysts, data scientists, and engineers in a fast-paced consulting setting.

Qualifications

• 5+ years as an Analytics Engineer or similar role.
• Strong SQL with dbt and data modeling experience.
• Experience building semantic layers and production deployments.
• Proficiency in Python for orchestration and tooling.
• Familiarity with BI tools that integrate semantic layers (Looker, Omni).

Responsibilities

• Design and maintain scalable data transformation pipelines with dbt and Airflow.
• Architect semantic layer for consistent downstream consumption and performance.
• Lead ETL/ELT framework development with robust data quality testing.
• Implement monitoring, logging, CI/CD, and alerting for pipeline health.
• Partner with client stakeholders to translate needs into data solutions.
• Guide analytics engineering practices and promote reusable data patterns.
• Collaborate with analysts, data scientists, and engineers on data models.
• Enforce data validation, contracts, and governance in model releases.

Tools

dbt

Airflow

SQL

Python

Git

Looker

Snowflake

Job description

# Senior Analytics EngineerFull-timeRemote (US)CompetitivePosted July 2026## OverviewWe’re looking for a driven, thoughtful, and intellectually curious Senior Analytics Engineer to join our core team at Astrodata. In this role, you’ll focus on designing and implementing data solutions that support ingestion, transformation, orchestration, and downstream delivery - serving a wide range of clients and technology partners.## Responsibilities* Design, implement, and maintain scalable and modular data transformation pipelines using tools like dbt and Airflow, ensuring reliable transformation, data quality enforcement, modeling layer construction, and delivery of robust consumption-ready data across diverse client environments.* Architect and optimize a flexible, business and agentic-friendly semantic layer for consistent downstream consumption - with consideration for performance, stakeholder needs and reliable analytical outputs.* Lead the development and orchestration of robust ETL/ELT frameworks, with a focus on reusability, observability, and testing practices (e.g., data contracts, dbt tests, test coverage, enabling teams to employ robust data quality and testing practices).* Proactively implement monitoring, logging, CI/CD practices, and alerting strategies to ensure pipeline health and resilience in production.* Serve as a strategic technical partner to client stakeholders across operations, finance, product, and executive teams - translating ambiguous needs into actionable data solutions.* Guide client teams on analytics engineering and modeling best practices, agile yet trustworthy delivery patterns, and how to leverage the modern data stack effectively.* Collaborate with client-side analysts, data scientists, and engineers to design shared data models, semantic layers, and analytics-ready datasets.* Design, define and enforce data validation and automated quality expectations and checks across data modeling layers and components of the stack, including data contracts and effective delivery downstream.* Implement data governance standards and practices within data model releases and team procedures, setting up clients for long-term success.* Establish and maintain metadata, documentation, and lineage tracking systems to ensure transparency and stewardship across evolving data ecosystems.* Provide technical leadership within project teams, mentoring junior engineers and championing high standards in code quality, testing, and review processes.* Stay current on evolving data tools and patterns; proactively propose new architectures and workflows to meet emerging client needs.* Lead or contribute to internal tooling, templates, and process improvements that strengthen the consultancy’s analytics engineering practice.## Requirements* 5+ years of experience as an Analytics Engineer (or similar role)* Significant experience designing and implementing dimensional modeling solutions end-to-end (e.g. planning and building staging models, conformed layers and marts) - from the design and agile development, to robust data testing and release management* Strong SQL experience, especially writing data transformations via dbt* Experience dimensional modeling (e.g. especially Kimball, others like Data Vault helpful)* Experience developing a semantic layer, and releasing semantic models to production* Experience working in BI tools, especially those which include or integrate directly with a semantic layer (e.g. Omni, Looker)* Python experience, especially orchestrating data pipelines via a workflow orchestration tool (e.g. Airflow, Prefect)* Experience using git for version control, and working within agile (e.g. Scrum) teams.* Excellent English language skills* Consulting experience preferred### Nice to Have* Experience productionizing data models used for serving downstream embedded analytics or AI applications* Understanding of the medallion architecture, building incremental history capture pipelines and change data capture (CDC) patterns in dbt* Experience with multiple data warehouse & platform technologies (e.g. Snowflake, DuckDB, Databricks, ClickHouse, BigQuery)* Experience with streaming event analytics pipelines and analytical use case (e.g. Snowplow data, clickstream data, analytics)* Experience working in healthcare or health technologies (and the security and privacy considerations for building solutions in such environments)* Experience working on marketing attribution data challenges, especially data-driven attribution and marketing mix modeling (MMM).## Benefits & Perks* Remote work with at least annual team offsite* Great health, dental, and vision coverage (US only)* 401k benefits with employer matching contribution (US only)* The chance to help build out our practice, helping form our service offerings and strategy* Ability to learn rapidly amongst an extremely talented and collaborative team* An awesome, empathetic community of co-workers## Apply Now