Analytics Engineer

Salary

$103,800 - $134,925

Location

Bellevue (Corporate Office), WA, Hybrid

Summary:

Analytics at AAA Washington is accelerating forward! As our first Analytics Engineer, you will play a pivotal role in shaping our next phase of growth by modernizing and architecting data pipelines and data products that serve as the bridge between raw data and critical insights. Collaborating closely with data scientists, business analysts, data/product engineering, and business stakeholders, you’ll ensure the accuracy, salience and usefulness, and reliability of our data to fuel descriptive and advanced analytics.

Essential Duties/Responsibilities:

Collaborate with business analysts, data scientists, data engineering, architects, and stakeholders to gather requirements and deliver scalable solutions
Develop and maintain data models that enable Descriptive and Advanced Analytics (predictive modeling, ML, etc.)
Design, build, and maintain scalable and efficient data pipelines using modern ETL, orchestration, and automation tools and techniques
Maintain comprehensive documentation for data pipelines, processes, and data models
Ensure data quality is maintained by executing data governance policies, procedures, and standards, including analysis and tools that monitor quality and pipeline performance
Partner with IT teams (Data Engineering and Data Architecture) to ensure alignment with enterprise data governance policies, procedures, and practices
Design data visualizations, dashboards, and reporting solutions that are informative, usable, salient, and reduce cognitive load
Contribute to a positive team dynamic through respectful interactions, positive contributions, and active collaboration to achieve department and organizational goals
Incorporate AAA’s vision, mission and values in day-to-day activities and behaviors; guides and motivates others to remain committed to AAA’s vision mission and values.

Minimum Qualifications:

Bachelor’s degree in informatics, statistics, computer science, mathematics, engineering, or related field or equivalent experience
3+ years’ experience in data engineering or analytics engineering roles
Advanced proficiency with SQL and Python
Experience with pipeline orchestration tools such as Azure Data Factory or Airflow
Experience with dimensional modeling and data warehousing
Hands-on experience with cloud provider integration and automation via CLIs and APIs
Experience with data visualization tools (e.g., Tableau, Power BI)

Preferred Qualifications:

1-2 years’ experience in travel, insurance, subscription membership, and/or service-related industries
Experience using dbt
Experience with Microsoft Fabric
Experience in modernizing data platforms, tools, or data products, including upgrading on-prem/legacy systems

Certificates, Licenses, Registrations:

Industry recognized certifications preferred

Knowledge, Skills, Abilities:

Strong expertise in data modeling, data integration, and data warehousing
Effective communication skills for communicating complex concepts to a non-technical audience
Strong business acumen to deliver contextual data solutions aligned with company goals and objectives
Ability to question assumptions and approach problems with a learning mindset
Skilled at managing competing priorities and project sizing
Agile and adaptable, able to handle rapidly changing tasks, shifting priorities, and transitions to new projects or assignments
Ability to work independently as well as collaboratively with team members and with partners across business units
Adept at building rapport and gaining trust

Work Environment & Physical Demands:

Hybrid work from home and office required
The physical environment is typical of a standard office space. It requires the employee to work inside for the duration of work. Must be able to remain in a stationary position, sitting for more than 50% of the time. This position will require occasionally moving about inside the office to access equipment, cabinets, etc. May work around office equipment which could be noisy, such as copiers and fax machines.

Other:

Equipment used: Computer, phone, various virtual technologies, other office equipment
Travel: Rarely Travel

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