Databricks Data Engineer | Senior

<h3>Accountabilities</h3><li>Design, build, migrate, and evolve data engineering solutions within Databricks environments.</li><li>Develop and maintain scalable, reliable, and high-performance data pipelines.</li><li>Implement data ingestion, transformation, and delivery processes using Apache Spark and PySpark.</li><li>Design and implement Data Lake and Data Lakehouse architectures using the Medallion model across Bronze, Silver, and Gold layers.</li><li>Translate business rules and requirements into efficient data processes and technical solutions.</li><li>Participate in data platform migration and modernization projects.</li><li>Configure and manage Databricks Jobs, Workflows, orchestration, and pipeline monitoring.</li><li>Implement data solutions using Delta Lake, Delta Tables, Unity Catalog, and Lakeflow Declarative Pipelines.</li><li>Support data ingestion initiatives using Lakeflow Connect and related technologies.</li><li>Ensure pipeline quality, performance, observability, reliability, and operational stability.</li><li>Apply version control, CI/CD, and software engineering best practices throughout the development and deployment lifecycle.</li><h2>Requirements</h2><li>Strong hands-on experience with<strong>PySpark, Apache Spark, and SQL</strong>.</li><li>Practical experience with<strong>Databricks</strong>, including Delta Lake, Delta Tables, Unity Catalog, and Lakeflow Declarative Pipelines.</li><li>Experience with<strong>Lakeflow Connect</strong>for data ingestion is desirable.</li><li>Experience with Databricks Jobs, Workflows, orchestration, and pipeline monitoring.</li><li>Solid understanding of<strong>Lakehouse architecture</strong>and the<strong>Medallion model</strong>using Bronze, Silver, and Gold layers.</li><li>Previous experience migrating data platforms or delivering data engineering projects using Databricks.</li><li>Knowledge of<strong>Git, CI/CD</strong>, and modern development and deployment practices.</li><li>Experience with or knowledge of technologies such as<strong>Airflow, Kafka, dbt, AWS Glue, and BigQuery</strong>.</li><li>Experience working with SQL and NoSQL databases, including technologies such as<strong>PostgreSQL, MongoDB, or Cassandra</strong>.</li><li>Strong analytical and problem-solving abilities, with the capacity to translate business requirements into scalable data solutions.</li><li>Ability to work collaboratively with technical and business stakeholders in data modernization initiatives.</li><li>Experience with accounting or financial projects is a plus.</li><li>
<strong>Databricks Certified Data Engineer Associate</strong>certification is considered an advantage.</li><h2>Benefits</h2><li>Remote work model.</li><li>Full-time employment.</li><li>Opportunity to work with modern data engineering technologies and Databricks-based Lakehouse architectures.</li><li>Exposure to large-scale data migration and modernization initiatives.</li><li>Opportunity to work with Spark, PySpark, Delta Lake, Unity Catalog, Lakeflow, and other cloud data technologies.</li><li>Professional development in a technology-driven environment focused on AI and modern digital platforms.</li><li>Opportunity to collaborate with experienced technology professionals on complex data engineering challenges.</li><li>Accessibility and inclusion: opportunities are also open to people with disabilities.</li>