Sqlmesh Engineer Jobs

1 job found

1mo ago

Senior Analytics Engineer, People Data

Anduril Industries Costa Mesa, CA

Costa Mesa, CA

1mo ago Closed

$166k - $220k/yr Full time Senior Analytics Apache Airflow

This position is no longer accepting applications (closed Jul 2, 2026).

Job Description

Senior Analytics Engineer, People Data based in Costa Mesa, CA (onsite) for Anduril Industries, with a salary range of USD 166,000 - 220,000 per year.

Responsibilities

Design, develop, and optimize end-to-end ETL and ELT pipelines to ingest, harmonize, and transform people data from HRIS, ATS, LMS, and other HR systems into the data platform.
Create and govern scalable, secure data models, schemas, and ontologies for people analytics, ensuring data quality and accessible downstream consumption.
Contribute to the strategic evolution of the people data platform and tooling, promoting engineering best practices, automation, and a scalable analytics ecosystem using SQLMesh, Iceberg, and Flyte.
Collaborate with People Analysts, HR Business Partners, and stakeholders to translate analytical needs into robust, well-documented datasets.
Implement and monitor data quality checks, troubleshoot data issues, and maintain data reliability across systems.
Monitor the performance of pipelines and models, identify bottlenecks, and implement improvements to support scalability and efficiency.
Document data pipelines, models, and processes; advocate for data engineering practices such as version control, testing, and CI/CD within the team.
Enforce data security measures and ensure compliance with internal policies and external regulations (GDPR, CCPA) for employee data privacy.
Collaborate with enterprise analytics and data engineering teams to align data architecture standards and integrate people data with other business domains.

Requirements

Minimum of 5 years of experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and infrastructure.
Advanced SQL expertise for complex data manipulation and proficient Python for scripting and automation.
Hands-on experience with cloud-based data warehouses (Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake storage (S3, Azure Data Lake Storage).
Strong background in designing and maintaining analytical data models, including dimensional modeling (Kimball).
Hands-on experience constructing and optimizing ETL/ELT pipelines with dbt, Apache Airflow, Flyte, Dagster, or similar orchestration tools.
Excellent written and verbal communication, with ability to translate technical concepts for non-technical partners and collaborate across teams.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
S solid foundation in data engineering with SQL, Python, and cloud platform experience (AWS, GCP, Azure).

Technologies

SQL
Python
Snowflake
Google BigQuery
AWS Redshift
Databricks/Delta Lake
AWS S3
Azure Data Lake Storage
dbt
Apache Airflow
Flyte
Dagster
Iceberg
SQLMesh
Palantir Foundry
Terraform
CloudFormation
Docker
Kubernetes
Tableau
Power BI
Looker
Rippling
Workday
Oracle HCM Cloud
Apache Spark
Flink

Benefits

Equity grants included in the majority of full-time offers and are considered part of Anduril's total compensation package.
Comprehensive benefits package for full-time employees, including health and recovery support.

Preferred Qualifications

Experience with big data processing frameworks such as Apache Spark and Flink, and with schema evolution or time travel features like Iceberg or Delta Lake.
Hands-on experience with Palantir Foundry, SQLMesh, Flyte, or similar modern data orchestration platforms.
Cloud provider certifications (for example, AWS Certified Data Analytics - Specialty or Google Cloud Professional Data Engineer).
Experience with infrastructure as code and containerization tools such as Terraform, CloudFormation, Docker, or Kubernetes.
Familiarity with integrating data pipelines with BI tools (Tableau, Power BI, Looker) to optimize dashboards and data accessibility.
Experience working with enterprise HRIS data sources (Rippling, Workday, Oracle HCM Cloud) and understanding their data models and APIs.
Strong understanding of HR data concepts, metrics, and HR systems (HRIS, ATS, LMS) with a focus on People Analytics.

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