Lead Analytics Architect

Ericsson • Santa Clara, CA

14h

About The Position

Contribute to both Data Engineering and Data Architecture, ensuring alignment with overall data strategy and business objectives. Design, evolve and own data warehouses and large-scale data platforms; deliver high-quality, production-grade data feeds. Build and maintain ETL/ELT jobs and end-to-end data pipelines; modernize the data stack using tools such as dbt, Informatica, Airflow and Snowflake. Implement AI-driven automation to optimize data workflows and improve data readiness for analytics and ML. Establish and refine data engineering standards, governance and delivery practices, lead architecture reviews and mentor engineering teams. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world's toughest problems. You´ll be challenged, but you won't be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. We truly believe this approach drives innovation, which is essential for our future growth. DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. They are not an exhaustive list of all responsibilities, duties and skills required for this position, and you may be required to perform additional job tasks as assigned.

Requirements

• Bachelor's degree in computer science or related field, or equivalent experience; advanced degree is a plus.
• 8+ years of experience as a Data Engineer or in a similar role with a proven track record delivering ETL/ELT jobs and pipelines.
• Strong expertise in data warehousing and data architecture and experience building modern data stacks (dbt, Informatica, Airflow, Snowflake, etc.).
• Proficiency in at least one programming language (Java, Scala, Python, etc.).
• Demonstrated ability to design and implement large-scale data solutions end-to-end and to lead architecture reviews and cross-team collaboration.
• Strong collaboration and communication skills to work with business stakeholders and cross-functional teams.

Nice To Haves

• Familiarity with AI-driven automation and metrics-driven delivery (OKRs) is highly desirable.

Responsibilities

• Contribute to both Data Engineering and Data Architecture, ensuring alignment with overall data strategy and business objectives.
• Design, evolve and own data warehouses and large-scale data platforms; deliver high-quality, production-grade data feeds.
• Build and maintain ETL/ELT jobs and end-to-end data pipelines; modernize the data stack using tools such as dbt, Informatica, Airflow and Snowflake.
• Implement AI-driven automation to optimize data workflows and improve data readiness for analytics and ML.
• Establish and refine data engineering standards, governance and delivery practices, lead architecture reviews and mentor engineering teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level