Design and implement data integration solutions in collaboration with the Solution Engineer and data architects
Support ingestion, transformation, and orchestration using ADF, Synapse pipelines, Databricks Workflows, and event‑based patterns
Implement batch, incremental, and event‑driven ingestion using agreed reference architectures
Maintain and extend data integration frameworks
Contribute to data modeling standards (Dimensional, Data Vault, Lakehouse)
Implement analytics‑ready models and semantic layers for BI and ML
Apply agreed data contracts and integration patterns
Implement data cataloging, lineage, and data quality controls
Apply RBAC, ABAC, encryption, and auditability controls
Optimize Databricks performance, cost, and storage layout
Monitor and troubleshoot pipelines and workloads
Support platform modernization, POCs, and migrations
Contribute to engineering standards and participate in design reviews
Partner with offshore teams, architects, and business stakeholders

Bachelor’s degree in Computer Science, Information Technology, or a numerate discipline
At least 5 years of experience in data engineering roles
At least 3 years of hands‑on Databricks and Delta Lake experience
Strong Azure data platform expertise (Databricks, ADF, Synapse, Event Hubs, Functions, ADLS Gen2, Key Vault, DevOps)
Proficiency in Spark, PySpark, and SQL
Experience implementing Medallion / Lakehouse architectures
Familiarity with data governance, Unity Catalog, and DQ frameworks
Understanding of security, compliance, CI/CD, and IaC (Bicep/Terraform)
MLOps and AI platform knowledge: MLflow, feature stores, model lifecycle and deployment patterns
Strong communication and collaboration skills

Data Engineer

Key skills