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This is an on-site position at Qualysoft located in Bucharest.

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Qualysoft is actively hiring for Data roles. Visit the company page to see all open positions and learn more about working at Qualysoft.

Senior Data Engineer (Banking)

Qualysoft Bucharest Today

data

About Qualysoft

· 25 years of experience in software engineering, established in Vienna, Austria

· Active in Romania since 2007, with office in central Bucharest (Bd. Iancu de Hunedoara 54B)

· Delivering End to End IT Consulting Services - From Team Augmentation and Dedicated Teams to Custom Software Development

· We deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms

· Cross-industry experience by sustaining global players in BSFI (Banking, financial services and insurance), Telecom,Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logitics, High Tech

· Global Presence: Switzerland, Germany, Austria, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia

· International team of 500+ software engineers

· Strategic partnerships: Microsoft Cloud Certified Partner, Tricentis Solutions Partner in Test Automation and Test Management, Creatio Exclusive Partner, Doxee Implementation Partner

· Powered by cutting-edge technologies: AI, Data & Analytics, Cloud, DevOps, IoT, and Test Automation.

· Project beneficiaries ranging from large-scale enterprises to startups

· Stable growth and revenue increase year over year, a resilient organisation in volatile IT market conditions

· Quality-first mindset, culture of innovation, and long-term client partnerships

· Global and local reach – trusted by key industry players in Europe and the US

Responsibilities

Design and implementation of robust, scalable, and high-performance ETL/ELT data pipelines using PySpark/Scala and Databricks SQL on the Databricks platform;

Strong expertise in implementing and optimizing the Medallion Architecture (Bronze, Silver, Gold) using Delta Lake, ensuring data quality, consistency, and historical tracking.

Efficient implementation of the Lakehouse architecture on Databricks, combining best practices from traditional Data Warehousing and Data Lake paradigms;

Optimization of Databricks clusters, Spark operations, and Delta tables (e.g. Z-Ordering, compaction, query tuning) to reduce latency and compute costs;

Design and implementation of real-time and near-real-time data processing solutions using Spark Structured Streaming and Delta Live Tables (DLT);

Implementation and administration of Unity Catalog for centralized data governance, fine-grained security (row- and column-level security), and end-to-end data lineage;

Definition and implementation of data quality standards and validation rules (e.g. using DLT or Great Expectations) to ensure data integrity and reliability;

Development and management of complex workflows using Databricks Workflows (Jobs) or external orchestration tools such as Azure Data Factory or Airflow to automate data pipelines;

Integration of Databricks pipelines into CI/CD processes using Git, Databricks Repos, and Databricks Bundles;

Close collaboration with Data Scientists, Analysts, and Architects to translate business requirements into optimal technical solutions;

Providing technical mentorship to junior engineers and promoting engineering best practices across the team.

Qualifications

Proven, expert-level experience across the full Databricks ecosystem, including Workspace management, cluster configuration, notebooks, and Databricks SQL.

In-depth knowledge of Spark architecture (RDDs, DataFrames, Spark SQL) and advanced performance optimization techniques;

Strong expertise in implementing and managing Delta Lake features, including ACID transactions, Time Travel, MERGE operations, OPTIMIZE, and VACUUM;

Advanced/expert proficiency in Python (PySpark) and/or Scala (Spark);

Expert-level SQL skills and strong experience with data modeling approaches (Dimensional Modeling, 3NF, Data Vault);

Solid hands-on experience with a major cloud platform (AWS, Azure, or GCP), with a strong focus on cloud storage services (S3, ADLS Gen2, GCS) and networking fundamentals.

Nice to have

Practical experience implementing and administering Unity Catalog for centralized governance and fine-grained access control;

Hands-on experience with Delta Live Tables (DLT) and Databricks Workflows for building and orchestrating data pipelines;

Basic understanding of MLOps concepts and hands-on experience with MLflow to support collaboration with Data Science teams;

Experience with Terraform or equivalent Infrastructure as Code (IaC) tools;

Databricks certifications (e.g. Databricks Certified Data Engineer Professional) are considered a significant advantage;

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field;

5+ years of experience in Data Engineering, including at least 3+ years working with Databricks and Apache Spark at scale.

What We Offer

· Premium medical package

· Lunch Tickets & Pluxee Card

· Bookster subscription

· 13th salary and yearly bonuses

· Enterprise job security with a startup mentality (diverse & engaging environment, international exposure, flat hierarchy) under the stability of a secure multinational

· A supportive culture (we value ownership, autonomy, and healthy work-life balance) with great colleagues, team events and activities

· Flexible working program and openness to remote work

· Collaborative mindset – employees shape their own benefits, tools, team events and internal practices

· Diverse opportunities in Software Development with international exposure

· Flexibility to choose projects aligned with your career path and technical goals

· Access to leading learning platforms, courses, and certifications (Pluralsight, Udemy, Microsoft, Google Cloud)

· Career growth & learning – mentorship programs, certifications, professional development opportunities, and above-market salary