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# Analytics Engineer

- **Company:** The Financial Times Ltd.
- **Location:** Sophia, WV, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Data Analysis, Automation of Tests, BigQuery, Collaborative Learning, Databases, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Migration, Data Visualization, Data Warehousing, Database Design, Database Queries, Github, Python (Programming Language), Microsoft SQL Server, Performance Tuning, Software Engineering, SQL Databases, Data Processing, Scripting, Data Build Tool (dbt), Data Analytics, Looker Analytics, Software Version Control, Data Pipelines, Service Stack, Amazon Redshift
- **Published:** October 14, 2026
- **Apply:** https://job-boards.eu.greenhouse.io/financialtimes33/jobs/5005449101

## About the Role

* 3+ years of experience in Analytics Engineering, BI, or Data Engineering roles.
 * Strong proficiency in SQL, including complex queries and performance tuning.
 * Hands-on experience with dbt for data transformation and modeling.
 * Understanding of data migration to cloud platforms such as AWS (Redshift) or GCP (BigQuery).
 * Familiarity with database design, version control (e.g. Git/GitHub), and CI/CD practices.
 * Experience with ETL/ELT tools (e.g. Airflow,DBT).

Personal skills

 * Strong analytical thinking and problem-solving abilities.
 * Effective communication skills and ability to collaborate across teams.
 * Attention to detail and focus on continuous improvement and data quality.
 * Adaptability to fast-paced environments.

Often used technology stacks and tools

 * Databases & Data Warehouses: AWS Redshift, BigQuery, MS SQL Server.
 * Data Transformation: dbt (data build tool).
 * ETL & Data Processing: Airflow.
 * BI & Data Visualization Tools: Looker.
 * Programming & Scripting: SQL, Python.
 * Version Control & DevOps: GitHub, CI/CD pipelines.
 * Cloud Platforms: AWS, GCP.

## Description

The Analytics Engineer is responsible for bridging the gap between data engineering and data analytics by maintaining and developing scalable data models and solutions that support finance, B2B, and B2C teams. The role plays a key part in delivering value through modern data stack technologies (including dbt), supporting cloud migration efforts, ensuring data quality, and maintaining the performance of analytical data pipelines., * Collaborate with stakeholders across departments to design and implement robust data models and BI solutions.

 * Build, test, and maintain data transformations using dbt (data build tool).
 * Implement software engineering best practices for data, including version control, CI/CD, and automated testing.
 * Deliver day-to-day support and project-related tasks for the data and BI infrastructure.
 * Develop and maintain scalable, maintainable, and well-documented data pipelines.
 * Identify and resolve issues across ETL/ELT processes and data pipelines., * 25 days paid leave
 * 24/7 Employee Assistance Program
 * Life Insurance
 * Enhanced Parental Leave policy
 * Food Allowance
 * Multisport Card
 * Both in house and external training programs
 * Your own training dedicated budget (for conferences, courses etc.)

We currently operate a hybrid model which requires staff to work onsite 50% of the time, subject to role requirements & regular review. While flexible working requests will be considered, not all patterns are suitable for all roles. We believe this balanced approach supports flexibility and protects our culture, making collaboration and communication easier, building stronger relationships and team cohesion, and supporting peer learning. We reserve discretion on reasonable notice to change this approach either generally or for specific individuals or teams.