Anduril Industries

Anduril Industries

Anduril Industries is an American defense technology firm that specializes in developing advanced autonomous systems for integrated awareness and security across land, sea, and air, utilizing its proprietary Lattice platform to enhance intelligence, su...

Aerospace & Defense
1K-5K
Founded 2017
$2200M raised

Description

  • Design, build, and optimize ETL/ELT pipelines to ingest, integrate, and transform people data from HR systems into the data platform.
  • Develop, maintain, and govern scalable and secure data models, schemas, and ontologies for people analytics.
  • Contribute to the design and evolution of the people data platform and tooling, advocating for automation and scalable analytics practices.
  • Partner with People Analysts, HR Business Partners, and other stakeholders to translate analytical needs into data solutions.
  • Implement and monitor data quality checks, troubleshoot data issues, and ensure data reliability and integrity across systems.
  • Continuously monitor pipeline and model performance, identify bottlenecks, and improve efficiency and scalability.
  • Create and maintain documentation for data pipelines, models, and processes while championing engineering best practices.
  • Implement and enforce data security measures and comply with internal policies and external privacy regulations.
  • Collaborate with enterprise analytics and data engineering teams to align on architecture standards and integrate people data with other domains.

Requirements

  • 5-7 years of progressive experience in Data Engineering, Analytics Engineering, or a similar role focused on data pipelines and infrastructure.
  • Expert-level SQL skills for complex data manipulation and querying.
  • Advanced Python skills for scripting, data processing, and automation.
  • Experience with cloud data warehousing platforms such as Snowflake, Google BigQuery, AWS Redshift, or Databricks/Delta Lake.
  • Experience with data lake technologies such as AWS S3 or Azure Data Lake Storage.
  • Proven experience designing and maintaining analytical data models, including dimensional modeling and Kimball methodology.
  • Hands-on experience building ETL/ELT processes with tools such as dbt, Apache Airflow, Flyte, Dagster, or similar orchestration platforms.
  • Excellent written and verbal communication skills with the ability to explain technical concepts to non-technical stakeholders.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
  • Preferred: Experience with big data frameworks such as Apache Spark or Flink.
  • Preferred: Experience with advanced data warehousing features such as schema evolution or time travel, including Apache Iceberg or Delta Lake.
  • Preferred: Hands-on experience with Palantir Foundry, SQLMesh, Flyte, or similar platforms.
  • Preferred: Professional cloud certifications such as AWS Certified Data Analytics - Specialty or Google Cloud Professional Data Engineer.
  • Preferred: Experience with Terraform, CloudFormation, Docker, or Kubernetes.
  • Preferred: Experience integrating data pipelines with BI tools such as Tableau, Power BI, or Looker.
  • Preferred: Deep experience with HRIS systems such as Rippling, Workday, or Oracle HCM Cloud, including their data models and APIs.
  • Preferred: Solid understanding of HR data concepts, metrics, and common HR systems such as HRIS, ATS, and LMS.

Benefits

  • US salary range of $146,000 to $210,000 USD base salary.
  • Highly competitive equity grants included in the majority of full-time offers.
  • Comprehensive, competitive benefits package available at little to no cost to employees.
  • Support for health, recovery, and future needs through the benefits package.
  • Top-tier benefits for full-time employees.
  • Compensation may vary based on experience, education, training, critical skills, and business considerations.

Interested in this position?

Apply directly on the company website

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