Data Engineer - Python/Azure Databricks

Role & Responsibilities :Key Responsibilities :

• Architect and implement enterprise-grade Lakehouse solutions using Databricks.

• Design and deliver scalable batch and real-time data pipelines using Apache Spark (PySpark/SQL).

• Build ETL/ELT pipelines, incremental data loads, and metadata-driven ingestion frameworks.

• Implement and optimize Databricks components: Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, and Workflows.

• Design large-scale data warehousing solutions with 3NF and dimensional modeling.

• Establish data governance, security, and data quality frameworks, including Unity Catalog.

• Lead ML lifecycle management using MLflow and drive AI use cases (RAG, AI/BI).

• Manage cloud-native deployments on Microsoft Azure and integrate with enterprise systems (e.g., ServiceNow).

• Drive CI/CD, DevOps practices, and performance optimization of Spark workloads.

• Provide technical leadership, mentor teams, and ensure successful delivery.

• Collaborate with stakeholders to translate business requirements into scalable solutions.

Ideal Candidate :

• Strong Databricks Architect Profile with end-to-end Lakehouse ownership.

• Mandatory (Experience 1) : Must have 10+ years of software engineering experience with at least 5+ years in Data Engineering with hands on exposure to Databricks and strong ownership of end-to-end data pipeline development.

• Mandatory (Experience 2) : Must have at least 5+ years of expertise across the Databricks ecosystem Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, Workflows, Unity Catalog.

• Mandatory (Tech skill 1) : Must have worked at architecture level, owning end-to-end design through deployment.

• Mandatory (Tech skill 2) : Must have strong experience with Python and SQL for data processing and Apache Spark for performance tuning & scalability.

• Mandatory (Tech skill 3) : Must have experience in large-scale data warehousing & advanced data modeling (3NF and dimensional) across batch and real-time systems.

• Mandatory (AI Exposure) : Must have at least a basic working understanding of how AI services or tools work.

• Mandatory (Communication) : Must have strong stakeholder management & requirement-gathering experience with US or UK clients.

• Mandatory (Company) : Must come from a B2B IT services or IT consulting background.