Senior Data Engineer

Remote.AR
Remote.Brazil
Remote.Bulgaria
Remote.Colombia
Remote.Poland
Rosario
Белград
Варна
Варшава
Вроцлав
Днепър
Киев
Клуж-Напока
Краков
Ларнака
Лвов
Лодз
Люблин
Монтевидео
Монтерей
Одеса
Рига
София
Харков

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Project overview

We are looking for a Senior Data Engineer to join a project focused on building a scalable and governed data platform in Databricks.

The role involves designing and implementing robust data pipelines, ensuring high data quality standards, and contributing to a well-structured medallion architecture (Bronze/Silver/Gold layers).

You will play a key role in building reliable, production-grade pipelines and shaping data architecture, governance, and best practices across the project.

Responsibilities

Design, build, and optimize data ingestion pipelines using Databricks
Implement and maintain Bronze, Silver, and Gold layers in a medallion architecture
Develop and enforce Data Quality (DQ) checks at each stage of data processing
Set up automated scheduling and incremental data loads (CDC) using Lakeflow
Configure and manage Unity Catalog, including governance policies, RBAC, and row-level security (RLS)
Ensure high data quality standards: ≥95% DQ pass rate, 100% schema conformity, and ≥99.99% primary key uniqueness during validation
Collaborate with SMEs and QA teams to align semantic data models
Implement monitoring and auditing pipelines for ingestion and transformation processes
Contribute to CI/CD processes for data pipelines and artifacts

Requirements

Strong experience with Databricks and modern data platform development
Hands-on experience with Delta Lake, Databricks Lakeflow (Declarative Pipelines), and Unity Catalog
Proficiency in SQL, PySpark, and Python
Experience with data quality frameworks and validation techniques
Solid understanding of data modeling, medallion architecture, and incremental data processing (CDC)
Experience with CI/CD tools and Git-based workflows
Strong problem-solving skills and attention to detail

Nice to have

Experience designing enterprise data governance frameworks
Background in building semantic layers for BI and reporting
Familiarity with data observability and monitoring tools

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