Analytics Engineer

Job Description

This job posting has expired and no longer accepting applications.

Position Overview:

We are looking for an Analytics Engineer to join our team here at ShyftLabs! The ideal candidate is someone who loves data and analytics and can both understand and develop overall business strategies. A blend of great technical skills and interpersonal skills is highly desirable in this role, which will be working alongside enterprise clients.

ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.

Job Responsibilities:

Develop, optimize, and maintain Looker and Power BI reports, ensuring usability, performance, and alignment with business objectives.

Lead and support the Looker migration and Power BI development, building robust data models, LookML structures, and interactive dashboards.

Design and maintain data pipelines and ETL processes, ensuring accurate, efficient, and scalable ingestion of data into Snowflake.

Collaborate with cross-functional teams to translate business requirements into scalable data solutions, focusing on automation and efficiency.

Optimize SQL queries, manage database performance, and implement best practices for data modeling and transformation.

Provide technical support and guidance to business teams, helping them interpret data and troubleshoot reporting issues.

Work with stakeholders to define KPIs and build actionable insights that drive strategic decision-making.

Basic Qualification:

5+ years of experience in analytics engineering, data engineering, or BI development.

Strong expertise in Looker (LookML, Explores, Dashboards) and Power BI (DAX, data modeling, dashboarding).

Proficiency in SQL, with experience optimizing queries and working with large datasets.

Hands-on experience with Snowflake or other cloud data warehouses (BigQuery, Redshift).

Experience developing and maintaining ETL pipelines and data transformation processes.

Proficiency in Python or another scripting language for automation and data manipulation.

Strong stakeholder engagement and client-facing experience, with the ability to explain technical concepts to non-technical audiences.

Experience working in Agile environments, with familiarity in version control (Git) and CI/CD best practices.

Excellent verbal and written communication skills, with a keen attention to detail.

Preferred Qualifications:

Client-facing experience is highly desired.

Working with Executive level shareholders is considered an asset.

Can identify ways to improve data quality and reliability.

Is aligned with the latest data trends or inconsistencies to simplify the data insights.

A commitment to teamwork with excellent interpersonal skills.

We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

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