Analytics Engineer – Digital Media
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Job Description
Analytics Engineer focused on analytics engineering and data modeling for a leading audiobook publisher. Building scalable data solutions and optimizing data infrastructure in a cloud-based environment.
Responsibilities:
- Design, build, and maintain scalable data models in Amazon Redshift to support reporting, dashboards, and ad hoc analysis.
- Collaborate with data engineering teams to expand and optimize the analytics warehouse architecture.
- Establish and enforce standards for schema design, naming conventions, and data lineage.
- Develop, maintain, and optimize data pipelines that deliver clean and reliable data to business users.
- Partner with stakeholders to gather requirements and translate business needs into scalable data solutions.
- Create and maintain comprehensive data documentation, including metrics definitions and transformation logic.
- Support BI platforms by ensuring analytics-ready datasets and assisting with dashboard development.
- Monitor data quality and implement testing, alerting, and validation processes to ensure warehouse reliability.
- Identify opportunities to improve data accessibility, consistency, and usability across the organization.
- Promote best practices in analytics engineering, including version control, code reviews, and reproducible workflows.
Requirements:
- 2–4+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence, Analytics, or Data Science.
- Strong SQL expertise with the ability to build efficient, scalable, and well-structured queries and data models.
- Hands-on experience with cloud data warehouse technologies, preferably AWS and Amazon Redshift.
- Proven ability to work directly with business stakeholders and translate reporting requirements into data architecture solutions.
- Experience with, or strong interest in, dbt and version-controlled SQL transformation workflows.
- Solid understanding of data modeling concepts, including dimensional modeling, star schemas, snowflake schemas, and slowly changing dimensions.
- Experience creating and maintaining clear data documentation, metric definitions, and data catalogs.
- Familiarity with BI tools such as AWS QuickSight, Tableau, Omni, or similar analytics platforms.
- Experience with Git and version control best practices for managing SQL, pipelines, and documentation.
- Strong problem-solving, communication, and analytical skills.
- Python experience for data pipelines, automation, or data engineering workflows is a strong plus.
Benefits:
- 100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.
- Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
- Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.
- Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
- Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.
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