Data Analytics Engineer

COMPANY BACKGROUND

LOVE.

It's what makes Subaru, Subaru®.

As a leading auto brand in the US, we strive to be More Than a Car Company®.

Subaru believes in being a positive force in the communities in which we live and work, not just with donations but with actions that set an example for others to follow.

That's what we call our Subaru Love Promise®.

Subaru is a globally renowned automobile manufacturer known for its commitment to innovation, safety, and sustainability.

With a rich history dating back to 1953, Subaru has consistently pushed the boundaries of automotive engineering to deliver vehicles that offer not only exceptional performance but also a unique blend of utility and adventure.

Subaru's company culture is built on collaboration, diversity, and a shared passion for our product.

We foster an inclusive environment that encourages employees to bring their unique perspectives and talents to the table.

Our team members are driven by a common goal: to create exceptional vehicles that inspire and delight our customers.

ROLE SUMMARY

The Data Analytic Engineer will be responsible for developing and optimizing cloud-based Business Intelligence solutions.

Advances data analytics capabilities and drives innovative solutions.

Possesses deep technical expertise in data engineering and plays instrumental role in managing data integrations from on-premises Oracle systems, Cloud CRM (Dynamics), and telematics.

Collaborates closely with Data Science and Enterprise Data Warehouse teams and business stakeholders.

Primary Responsibilities:

Data Ingestion and Storage:


* Designs, develops, and maintains scalable, efficient data pipelines using Data Factory, and Databricks, leveraging Py Spark for complex data transformations and large-scale processing.


* Builds and manages extract, transform, and load (ETL)/extract, load, transform (ELT) processes to seamlessly extract, transform, and load data from on-premises Oracle systems, customer relationship management (CRM) technology, and connected vehicles into data storage solutions, such as Data Lake Storage and SQL Database.

Data Engineering:


* Creates high-code data engineering solutions using Databricks to clean, transform, and prepare data for in-depth analysis.


* Develops and manages data models, schemas, and data warehouses, utilizing Lakehouse Architecture to enhance advanced analytics and business intelligence.


* Leverages Unity Catalog to ensure unified data governance and management across the enterprise's data assets.


* Optimizes data storage, retrieval strategies, and query performance to drive scalability and efficiency in all data operations.

Data Integration:


* Integrates and harmonizes data from diverse sources including on-premises databases, cloud services, application programming interfaces (APIs), and connected vehicle telematics.


* Ensures consistent data quality, accuracy, and reliability across all integrated data sources.

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