11/04/2026 updated

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Data Engineer | Databricks · PySpark · Microsoft Fabric · Azure · Snowflake

Pristina, Kosovo
Only remote
B.Sc. Computer Science and Engineering (UBT, in progress)
Pristina, Kosovo
Only remote
B.Sc. Computer Science and Engineering (UBT, in progress)

Profile attachments

Vlera_Saraci_CV.docx

About me

Data Engineer with 4 years building cloud data platforms on Databricks, Microsoft Fabric, Azure, GCP, AWS and Snowflake. PySpark, Delta Lake, SQL, Python; lakehouse/medallion, data modeling, data quality, cloud migration, GenAI/RAG pipelines. Certified Databricks DE, GCP ACE, Claude Architect

Delta LakeAzure DevOpsAmazon Web ServicesData AnalysisAutomationMicrosoft AzureBusiness IntelligenceBig DataGoogle BigQueryBusiness AnalysisCloud ComputingCloud EngineeringData ArchitectureData CleansingData GovernanceData InfrastructureData IntegrationExtract Transform Load (ETL)Data TransformationData ProfilingData VisualizationData WarehousingPython (Programming Language)PostgreSQLQuality ManagementMicrosoft Power BIDataOpsAzure Data LakeSQL DatabasesStatisticsSalesforce TableauModelling SkillsData ProcessingGoogle CloudData Storage TechnologiesCloud Platform SystemAzure Data FactorySnowflakeApache SparkGenerative AIGitMicrosoft FabricData LakePySparkData LineageAzure Data AnalyticsAzure Synapse AnalyticsStream AnalyticsData PipelineDatabase AdministrationKpi ReportingDatabricks
• Data Engineering: lakehouse architecture, medallion layering (bronze/silver/gold), batch and streaming pipelines, ETL/ELT, data modeling (dimensional, SCD2), data warehousing, event-driven patterns, structured and unstructured ingestion, cloud migration and re-platforming
• Spark & Lakehouse: Apache Spark, PySpark, Spark SQL, Structured Streaming, Delta Lake, Auto Loader, Unity Catalog, Lakeflow, Spark performance tuning (partitioning, Z-ordering, file compaction, join and query tuning)
• Programming: Python, SQL, PySpark, REST APIs
• Cloud & Platforms: Databricks, Microsoft Azure (Data Factory, Synapse, Data Lake Storage, Azure Databricks), Microsoft Fabric (Lakehouse, Pipelines), Google Cloud Platform (BigQuery, Cloud Storage, Pub/Sub, Compute Engine), AWS (S3, EC2), Snowflake (Snowpipe, Streams and Tasks, Dynamic Tables), multi-cloud
• Orchestration & DevOps: Databricks Workflows, Azure Data Factory, Fabric Pipelines, Git, CI/CD (Azure DevOps), n8n
• Data Quality & Governance: data quality rules and reconciliation, observability (freshness, volume, SLA monitoring, alerting), data lineage, RBAC and masking policies, source-to-target mapping, GDPR-aware data handling
• GenAI & AI Data: RAG pipelines, LLM data preparation, Snowflake Cortex (Search, Analyst, Agents), LLM-powered automation and migration accelerators, model-ready datasets
• BI & Analytics: Power BI, Tableau, KPI dashboards, Power Query, statistical analysis
• Databases: PostgreSQL, MySQL, NoSQL
• Ways of Working: Agile, requirements discovery, stakeholder partnership, business process analysis, cross-functional collaboration with data scientists, analysts and business teams
• Certifications: Databricks Certified Data Engineer Associate, Google Cloud Associate Cloud Engineer, Claude Certified Architect – Foundations (Anthropic)
• Languages: Albanian (native), English C1, German C1

Experience

Professional experience0 - 5 years
Freelancer since2024

Languages

GermanFluentEnglishFluentAlbanianNative speaker

Project history

Data Engineer

Genpact
• Build and maintain production batch and near-real-time pipelines with PySpark, Spark SQL, and Delta Lake (Structured Streaming, Auto Loader, incremental loads) on Databricks and Microsoft Fabric
• Implement lakehouse architecture with medallion layering (bronze, silver, gold) and dimensional/SCD2 data models delivering curated datasets for reporting, analytics, and ML
• Set up data quality, governance, and observability: rule-based validation, freshness and volume checks, SLA monitoring and alerting, Unity Catalog RBAC and lineage
• Optimize Spark and Delta workloads (partitioning, Z-ordering, compaction, join and query tuning) and orchestrate jobs with Databricks Workflows, cutting processing time and compute cost
• Work with stakeholders, analysts, and data scientists to challenge assumptions and propose simpler, more scalable alternatives before building; document pipelines, lineage, and data definitions
• Developed an LLM-powered migration accelerator that re-platforms legacy BI and ETL workloads into PySpark and Lakeflow pipelines on Databricks, with human review gates, automated validation, and cost tracking
• Built Snowflake ELT pipelines (Snowpipe, Streams and Tasks, Dynamic Tables, SCD2, RBAC and masking policies) and GenAI assistants using RAG and agents with Snowflake Cortex (Search, Analyst)

Data Engineer & Analyst

Deehive
• Led data engineering on SPAR, Deehive's flagship project: architected a Spark/PySpark lakehouse on Azure and Microsoft Fabric (Fabric Lakehouse, Delta tables) for high-volume batch and near-real-time ingestion, cleansing, and delivery of model-ready data for AI and analytics
• Defined and maintained data quality rules and controls (completeness, validity, consistency) across 10+ sources, with automated alerting on rule breaches and data freshness
• Designed and orchestrated ETL/ELT workflows with Azure Data Factory, SQL, and Python, reducing reporting turnaround from days to hours
• Introduced Git-based versioning and CI/CD (Azure DevOps) for pipelines and notebooks, removing manual deployment steps and keeping dev, test, and prod consistent
• Used Azure Data Lake Storage, Azure Databricks, and Synapse to build scalable storage, processing, and serving layers for BI, analytics, and data science teams
• Delivered Power BI data products that became the primary tool for performance monitoring, customer segmentation, and KPI tracking across the company

Assistant Manager & Data Analyst

CIKAT N'STEM
• Managed end-to-end data collection, validation, and reporting across multiple projects, and built standardized reporting templates that reduced onboarding time and improved consistency

Data Engineer

AnchorzUp
• Led a cloud migration program from legacy on-premise systems to GCP and Azure, re-platforming pipelines and data models with source-to-target mappings and data flow diagrams, and delivering a zero-downtime cutover
• Partnered with business stakeholders to understand why legacy processes existed, surfaced gaps and better alternatives instead of lifting-and-shifting as-is, and designed target data models for the new cloud architecture
• Built data validation and reconciliation workflows in SQL and Python to verify migration integrity across legacy and new systems, establishing data quality rules for post-migration assurance
• Designed automated, event-driven integration workflows to keep data synchronized between legacy systems and cloud platforms (BigQuery, Cloud Storage, Pub/Sub, Microsoft Fabric, Azure), significantly reducing manual intervention
• Developed Power BI reports and dashboards for migration monitoring, post-migration KPI tracking, and ad hoc analysis used by management for operational validation

Certificates

Databricks Certified Data Engineer Associate

Databricks

2026

Google Cloud Associate Cloud Engineer

Google Cloud

2026

Claude Certified Architect – Foundations

Anthropic

2026

Portfolio

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