Analytics Engineer

Job not on LinkedIn

🔥 6 minutes ago

⛷️ Utah – Remote

⛷️ Utah – Remote

💵 $100k - $140k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Analytics Engineer

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Verisk

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1971

💼 Consulting

🏗️ Construction

📦 Logistics

💰 $500M Post-IPO Debt on 2023-03

Consulting • Construction • Logistics

Verisk is a company that specializes in providing advanced data analytics, technology, and scientific research to the global insurance industry. It delivers solutions across various insurance sectors such as Property & Casualty, Life and Annuities, Reinsurance, and Specialty Markets, helping clients to assess and price risks with speed and precision. Verisk's offerings include underwriting and rating support, claims management, compliance, catastrophe risk modeling, and insights into extreme event risks. Additionally, Verisk serves other industries such as construction, real estate, and transportation by offering data-driven insights and solutions for risk assessment and business optimization, while also contributing to sustainability and resilience initiatives through its research and analytics.

📋 Description

• Research and work with business stakeholders to develop our data warehouse model. • Clean, transform, and enrich data to create high-quality datasets suitable for analysis and machine learning. • Work closely with product teams, software developers, data scientists, and analysts to understand data needs and deliver innovative solutions. • Ensure data accuracy, consistency, and reliability across all datasets. • Optimize data processes for performance and scalability. • Maintain comprehensive documentation of transformation logic and lineage.

🎯 Requirements

• Bachelor’s degree in computer science, Data Engineering, or a related field. • 3+ years of experience as an Analytics Engineer or in a similar role. • Strong Communication skills: Ability to work with technical and non-technical audiences to translate business requirements into data models. • Data Warehousing: Knowledge of data warehousing concepts and solutions (e.g., Redshift, Snowflake). • Data modeling: experience in modern data modeling practices, ideally dimensional modeling. • Programming Languages: Proficiency in SQL and a familiarity with Python. • Data Processing: Experience with ETL tools and frameworks (e.g., Apache Airflow, Luigi, DBT). • Database Management: Strong knowledge of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra). • Version Control: Proficient with version control systems (e.g., Git). • Machine Learning: Understanding of machine learning concepts and experience working with data for ML model training. • AI: Familiarity and enthusiasm for bleeding-edge analytical enablement using tools such as Large Language Models and Prompt Engineering.

🏖️ Benefits

• Health Insurance • Retirement Plan • Disability benefits • Paid Time Off