Data Engineer jobs in Bulgaria
Explore 5 matching jobs.
Senior Data Engineer
Valtech
Posted: 10/21/2026AirflowApacheAWSAzureCloudDistributed SystemsGoogle Cloud PlatformKafkaPython+4 more
Data Engineering Consultant
The Coca-Cola Company
Posted: 10/8/2026Cloud
Senior Data Engineer
EC Markets
Posted: 10/7/2026AWSETLPythonSQLTerraform
BI & Data Platform Lead
Commit
Posted: 9/25/2026AirflowAmazon RedshiftBigQueryETLGoogle Cloud PlatformPythonSQLTableau
Data Engineer – Enterprise Data & Intelligence
Fourth
Posted: 9/21/2026ApacheAzureCloudETLKafkaPySparkPythonSQL
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and optimizing cloud-based data platforms, with strong capabilities in building and managing data pipelines using Apache Spark, Delta Lake, and Databricks. Proficient in data modeling, governance, and ensuring data quality across various cloud environments.
Highest-signal resume keywords
Apache SparkDelta LakeDatabricks Lakehouse PlatformPythonSQL
Tech Stack
Tools & technologiesAirflowApacheAWSAzureCloudDistributed SystemsGoogle Cloud PlatformKafkaPythonSparkSQLTerraformUnity
About the role
Key responsibilities & impact- Design, build, and optimize modern cloud-based data platforms powering analytics, AI, and data products
- Develop reliable batch, streaming, and near-real-time pipelines using Spark and Delta Lake
- Build ingestion, transformation, and curation workflows for structured and unstructured data
- Implement lakehouse patterns and medallion layering across bronze, silver, and gold layers
- Contribute to cloud-to-cloud migrations, including re-platforming pipelines and data models
- Deliver production-grade datasets for analytics, machine learning, causal modeling, and optimization
- Build data pipelines for GenAI use cases, including LLMs, RAG, vector-based data flows, and agent-based architectures
- Leverage Databricks MLflow and Unity Catalog or equivalent tooling
- Design logical and physical data models
- Orchestrate workflows with Databricks Workflows, Airflow, dbt, or equivalents
- Apply event-driven and streaming architecture patterns
- Ensure data governance, lineage, quality, and access control using Unity Catalog, AWS Lake Formation, Microsoft Purview, or GCP Dataplex
- Establish observability for data freshness, pipeline reliability, and SLA adherence
- Enable serving layers such as APIs, feature inputs, and analytical endpoints
- Optimize pipelines and infrastructure for performance, scalability, and cost
- Understand stakeholder needs, challenge requirements, and surface better alternatives
- Collaborate with data scientists, ML engineers, analysts, platform teams, and business stakeholders
- Support adoption of data products and contribute to best practices
Requirements
What you’ll need- Experienced Senior Data Engineer
- Strong hands-on experience with Apache Spark and Delta Lake
- Strong Python and SQL
- Proven experience building batch and streaming pipelines and production-grade data platforms
- Solid understanding of data modeling, data quality, and governance
- Strong, demonstrable hands-on experience with the Databricks Lakehouse Platform
- Deep expertise in at least one major cloud: AWS, GCP, or Azure/Fabric
- Openness and ability to work across clouds
- Experience with lakehouse architectures and distributed systems
- Strong understanding of scalability, reliability, and performance
- Naturally curious, with strong problem-solving skills and a collaborative approach in cross-functional teams
- Comfortable challenging business requirements
- Adaptable and eager to work across platforms
- Agile or consulting experience is beneficial
- Nice-to-have: experience across more than one cloud or cloud migration experience
- Nice-to-have: Snowflake experience
- Nice-to-have: GenAI and AI data systems, including RAG pipelines, vector databases, and LLM data preparation
- Nice-to-have: CI/CD for data pipelines and infrastructure-as-code, including Terraform and CloudFormation
- Nice-to-have: streaming technologies such as Kafka, Spark optimization, or ML/experimentation platforms
- Nice-to-have: experience building data products or large-scale analytics platforms
Benefits
Comp & perks- Flexibility, with hybrid work options and 25 vacation days for a healthy work-life balance
- Co-subsidized transportation & Multisport cards
- Premium health insurance for fast and easy access to top healthcare services
- Training policy for technical and other skills-related events, courses and certifications
- Personal career development roadmap guided by performance evaluations
- Self-care program offering psychological consultations & discussions for you and the team
- Cozy office space designed for comfort and productivity
- Exciting team events and company gatherings
- Growth opportunities
- Values-driven culture
- International careers
- Inclusive culture and accessibility support
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingData QualityBatch PipelinesStreaming PipelinesCloud MigrationLakehouse ArchitecturesEvent-Driven ArchitectureCI/CD for Data PipelinesTerraformCloudFormation
Soft Skills
Problem-SolvingCollaborationAdaptabilityCuriosityChallenging Requirements
Tools & Technologies
Databricks MLflowUnity CatalogAWS Lake FormationMicrosoft PurviewGCP DataplexAirflowDbtKafkaGenAIRAG Pipelines
Industry Keywords
Cloud-Based Data PlatformsAnalyticsAI Data SystemsDistributed SystemsScalabilityReliabilityPerformance
