Data Engineer - Databricks and Banking Solutions - Tieto Tech Consulting (m/f/d)

Tieto · tieto.com

Sofia, Bulgaria Full-time 6 days ago
Workplace
On-site
Location
Sofia, Bulgaria

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About the role

Job Description

Tieto Tech Consulting (MentorMate from 2001 to 2026) provides design-led, data-centric, and AI-powered digital engineering & consulting services to enterprises worldwide. With a strong heritage of Nordic quality, local presence, and global-scale operations, we are backed by 8,500+ IT professionals. Our clients trust us for advanced data and analytics skills, top industry-specific expertise, specialized software R&D, and the capabilities of a multinational team. We are part of Tieto, a leading technology company with an annual revenue of approximately EUR 2bn.

Tieto Tech Consulting’s team in Bulgaria consists of 500+ professionals specializing in the development of tailored digital solutions in diverse industries.

We are looking for a Data Engineer with experience in Databricks and Azure to join our growing data engineering community. In this role, you will help design and implement modern data platforms, scalable data pipelines, and analytics solutions that enable organizations to make better data-driven decisions. You will work closely with data architects, BI developers, and customer stakeholders, working in an Agile environment to deliver reliable and high-quality data solutions.

Key responsibilities

* Develop and maintain scalable ETL/ELT pipelines using Databricks, Spark/PySpark and SQL * Build lakehouse and data platform solutions for Banking and Financial Services * Integrate data from multiple enterprise and banking systems and transform requirements into reliable data pipelines and models * Build analytics-ready datasets supporting financial and regulatory reporting * Implement data quality, reconciliation, lineage and monitoring for critical financial data * Optimize Spark workloads, Delta tables and pipeline performance * Support modernization and migration from legacy ETL/data warehouse solutions * Apply engineering practices for sensitive and governed data, including access controls and traceability * Collaborate with architects, analysts, SMEs and customer stakeholders in an Agile environment

Required experience & qualifications

* 2+ years of professional experience in Data Engineering or a similar role * Strong SQL and Python/PySpark skills * Hands-on experience with Databricks and Apache Spark * Experience developing ETL/ELT pipelines and data integration solutions * Experience with Azure or another major cloud data platform * Good understanding of data lakes, data warehouses and data modeling * Experience with data quality, testing, monitoring and performance optimization * Familiarity with Git, code reviews and CI/CD practices * Ability to translate business requirements into technical solutions * Excellent spoken and written English

A significant advantage would be

* Experience and domain knowledge in Banking or Financial Services * Experience with data platform modernization, ETL or data warehouse migration projects * Relevant certifications in Databricks, Azure, or AWS * Experience working in international environments ‌

Additional Information

At Tieto, we believe in the power of diversity, equity, and inclusion. We encourage applicants of all backgrounds, genders (m/f/d), and walks of life to join our team, as we believe that this fosters an inspiring workplace and fuels innovation. Our commitment to openness, trust, and diversity is at the heart of our mission to create digital futures that benefit businesses, societies, and humanity. Diversity, equity and inclusion | Sustainability | Tieto

Stay alert to recruitment scams: • Tieto only communicates via @tieto.com email addresses. • We never ask candidates to pay fees or share financial details during recruitment. • If you receive a suspicious message claiming to be from Tieto, don't respond — verify it via our official careers site. • For more information visit Important Advisory Regarding Recruitment Fraud | Tieto Blog

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  • SQL 79%
  • Python 79%
  • ETL 75%
  • Data modeling 50%
  • Data quality 49%
  • AWS 47%

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