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Financialtimes33

Analytics Engineer

Sofia

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hirly's read of this role

Role family
Data & ML
Seniority
Mid level
Country
BG
Work mode
Remote-friendly
First seen by hirly
14 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

About us

The Financial Times is one of the world’s leading news organisations, globally recognised for its authority, integrity and accuracy, with a mission to deliver quality information and services worldwide.

At the FT, curiosity thrives and ambitious thinking is rewarded. Here, you’re given the chance to reach millions, create work that matters and deliver impartial journalism in a polarised world.

In our warm, collaborative culture, you’ll connect with a diverse community of experts who support your growth, career aspirations and wellbeing.

Your future at the FT will be filled with opportunities that challenge and inspire you. With no fixed path, you’ll discover new skills and forge a career that can take you anywhere.

Build a newsworthy career at the FT.

Our commitment to diversity, equity and inclusion

We believe in the power of unique perspectives and want all voices in our organisation to be heard, respected and valued. A supportive workplace is one where employees feel they can be themselves and operate to their full potential. We are committed to removing barriers for everyone, with a focus on addressing those faced by underrepresented groups.

The role

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.

Key responsibilities

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.

Required skills and experience

Essential

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.

What’s in it for you? Our benefits

Annual bonus scheme

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.

Accessibility

We are a disability confident employer and Valuable 500 signatory.

Please let us know if you require any reasonable adjustments/personalisation as part of the application process or to enable you to attend an interview. If you would like to discuss your requirements or have any questions, email [email protected] and a member of our team will be happy to help.

Further information

At the FT, we embrace innovation and the use of technology and appreciate that individuals may leverage AI tools as part of their job application process. Whilst we are happy for you to use AI to assist with your application, it is essential that all information provided is authentic and accurately represents your skills, experience, and qualifications.

Candidates should be aware that the use of AI throughout the application process may be monitored to ensure a fair and transparent hiring process for all.

Please beware of fraudulent job postings and offers claiming to be from the Financial Times. All legitimate opportunities will direct you to apply through the official Financial Times careers site, and the FT will never ask for financial information, payments, or referrals to third parties during the hiring process. If you have any concerns about the legitimacy of a job posting or suspect any scam activity, please contact [email protected].

Interested in the FT but don’t see the right role yet? Join our Talent Community to receive exclusive updates, featured jobs, and insights into working at the FT.

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Original posting on Financialtimes33's site ↗

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