Senior Data Engineer(Azure-Databricks)

We are seeking an experienced Senior Data Engineer - Azure & Databricks with a proven track record (8+ years) of designing, building, and scaling modern data platforms within the Azure ecosystem.

This role is ideal for someone who thrives in complex enterprise environments, is deeply hands-on with Databricks and Spark, and can lead end-to-end data engineering initiatives from architecture to implementation.

You will be responsible for building robust, high-performance data pipelines, establishing engineering best practices, and collaborating with cross-functional teams to deliver reliable, scalable data solutions across both batch and Real Time streams., * Architect, design, and implement scalable data platforms and pipelines using Azure and Databricks.

• Build and optimise ingestion, transformation, and processing workflows for batch and Real Time (streaming) use cases.
• Work extensively with ADLS, Delta Lake, and Spark (Python/PySpark) to enable large-scale data engineering capabilities.
• Lead the development of complex ETL/ELT pipelines, ensuring performance, reliability, and code quality.
• Design conceptual, logical, and physical data models to support analytics and operational workloads.
• Work with relational and lakehouse systems, including PostgreSQL and Delta Lake.
• Define, implement, and enforce best practices for data governance, security, quality, and architecture standards.
• Partner closely with architects, data scientists, analysts, and business teams to translate requirements into scalable technical solutions.
• Troubleshoot production issues, drive performance optimisation, and support continuous platform improvements.
• Mentor junior engineers and contribute to the creation of reusable components and engineering standards.

• 8+ years of hands-on data engineering experience in enterprise environments.
• Strong expertise in Azure services, particularly Azure Databricks, Azure Functions, and (preferably) Azure Data Factory.
• Advanced proficiency in Apache Spark with Python (PySpark).
• Strong SQL skills, including query optimisation and performance tuning.
• Deep experience with ETL/ELT methodologies, scheduling, and data orchestration.
• Hands-on expertise with Delta Lake (ACID, schema evolution, performance tuning).
• Strong understanding of data modelling (normalised, dimensional, lakehouse).
• Proven experience with batch and streaming technologies such as Kafka or Event Hub.
• Solid grasp of data architecture, distributed systems, and cloud-native design patterns.
• Ability to design and evaluate end-to-end technical solutions and recommend best-fit architectures.
• Excellent analytical, problem-solving, and communication skills.
• Ability to collaborate across teams and lead technical discussions.

Preferred Skills:

• Experience with CI/CD tools such as Azure DevOps and Git.
• Familiarity with Infrastructure-as-Code (Terraform, ARM).
• Exposure to data governance and metadata cataloguing tools (eg, Azure Purview).
• Experience supporting machine learning or BI workloads on Databricks.

For Full-Time, Regular Employees

• Minimum 10 days paid vacation annually
• 6 days paid sick leave (prorated for new hires)
• 10 paid holidays
• Paid bereavement and jury duty leave
• Eligibility for 401(k) Retirement Plan with employer match
• Medical, dental, and vision insurance eligibility (employee + dependents)
• Company-paid:
• Basic life insurance
• Accidental death & disability coverage
• Short- and long-term disability
• Access to HSA and FSA programs (healthcare, dependent care, commuting)