Analytics Engineer 2

Job Summary: The Analytics Engineer 2 provides clean data sets and models data in a way that enables for analysis to be carried out to drive key business insights. The Analytics Engineer 2 provide business users with answers to their questions by creating data based analysis as required. The Analytics Engineer 2 has a general understanding of the data infrastructure and tooling and can leverage this for monitoring and maintaining data pipelines and developing data transformations to generate fresh reliable data assets.

Minimum Qualifications:

• Bachelor's degree or equivalent experience
• Experience in one or more major data subject areas (Product Marketing Sales Finance People etc.)
• Extensive experience working as part of a data team; preferably as either an experienced data engineer or data analyst
• Experience with Cloud Platforms (AWS Azure GCP etc.)
• Worked with cloud data warehouses for storing data (Snowflake BigQuery Redshift)
• Hands on experience with modern BI tools (Looker Mode Tableau or PowerBI)
• Modeling with Dataform dbt or another data modeling tool for data transformation
• Fundamental data architecture and design skills
• Microsoft Windows and Office proficient
• Good oral and written communications skills that demonstrate a professional demeanor and the ability to interact with others with discretion and tact
• Good organizational multi-tasking and time management skills
• Good collaboration skills applied successfully within team as well as with all levels of employees in other areas
• Good Microsoft Excel skills
• Good facilitation and project management skill
• Good interpersonal skills; able to maintain solid rapport with team members as well as maintain professionalism with those outside of department
• Good data gathering interviewing and analytical/problem solving skills
• Good critical thinking and problem solving skills
• Demonstrated proficiency with data system design including databases schema marts aggregates and views
• Ability to use original thinking to translate goals into the implementation of new ideas and design solutions
• Self-motivated with the ability to manage projects to completion with minimal oversight
• Able to thrive in a fast paced deadline driven environment
• Good attention to detail
• Demonstrated ability to influence motivate and mobilize team members and business partners
• Good ability to develop and use engaging informative and compelling presentation methodologies
• Good ability to handle sensitive information with discretion and tact
• Good ability to establish rapport and gain the trust of others; effective at gaining consensus
• Ability to work independently and in a team environment
• Good knowledge of SQL and strong data transformation skills
• Good knowledge of Microsoft Operating systems and products
• Enjoys working with emerging technologies
• Up to 5% travel time required

Responsibilities:

• Collaborate with team members to collect business requirements define successful analytics outcomes and design data models while considering non-functional requirements such as performance constraints cost constraints and security policies.
• Model design develop test and implement appropriate backend and front-end structures needed to meet business visualization and reporting requirements.
• Configure SaaS tools such as ELT providers integration platforms and orchestration tools to meet system requirements to build a modern cloud data warehouse that is accurate reliable high performing and easily accessible to our business departments.
• Provide day-to-day support of the data warehouse and associated data marts including establishing trusted data sets for common data with supporting documentation.
• Coordinate with the platform data engineering team data analyst teams data governance teams and IT teams to align with change management processes and to ensure performance processes and access is optimal for global reporting solutions.
• Improve processes regarding data flow and quality to improve data accuracy viability and value including testing small chunks of data transformations for correspondence to the set tasks.
• Understand business/department needs and goals and creating data-driven analysis and insight to support management decisions.