Lead Data Platform Engineer

NEXERA CONSULTING LLC
6 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Tech stack

API
Automation of Tests
Azure
Continuous Integration
Data as a Services
Information Engineering
Data Governance
Data Infrastructure
Data Integration
ETL
Data Systems
Data Warehousing
DevOps
Hive
Python
Nagios
Release Management
Standard Sql
Systems Integration
Data Logging
Data Processing
Cloud Platform System
Microsoft Power Automate
Azure
PySpark
Infrastructure Automation Frameworks
Information Technology
Deployment Automation
Data Management
Data Lakehouse
REST
Terraform
Data Pipelines
Serverless Computing
Databricks

Job description

The Data Platform Engineer designs, develops, automates, and maintains secure, scalable, and compliant data platforms that enable the firm to efficiently manage, analyse, and utilise data. The role ensures that data solutions are robust and reliable while meeting regulatory obligations and safeguarding client confidentiality., * Design and architect scalable, secure, and compliant data platforms and solutions, producing technical documentation and securing approvals through governance bodies such as Architecture Review Boards.

  • Build and deliver robust data solutions using Databricks, PySpark, Spark SQL, Azure Data Factory, and Azure services.
  • Develop APIs and write efficient Python, PySpark, and SQL code to support data integration, processing, and automation.
  • Implement and manage CI/CD pipelines and automated deployments using Azure DevOps to enable reliable releases across environments.
  • Develop and maintain infrastructure-as-code (eg, Terraform, ARM) to provision and manage cloud resources, including ADF pipelines, Databricks assets, and Unity Catalog components.
  • Monitor, troubleshoot, and optimise data platform performance, reliability, and costs, identifying bottlenecks and recommending improvements.
  • Create dashboards and observability tools to report on platform performance, usage, incidents, and operational KPIs.

Requirements

  • Degree in Computer Science, Data Engineering, or a related field.
  • Proven experience designing and building cloud-based data platforms, ideally within Azure.
  • Strong hands-on expertise with Databricks, PySpark, Spark SQL, and Azure Data Factory.
  • Solid understanding of Data Lakehouse architecture and modern data platform design.
  • Proficiency in Python for data engineering, automation, and data processing.
  • Experience developing and integrating REST APIs for data services.
  • Strong DevOps experience, including CI/CD, automated testing, and release management for data platforms.
  • Experience with Infrastructure as Code tools such as Terraform or ARM templates.
  • Knowledge of data modelling, ETL/ELT pipelines, and data warehousing concepts.
  • Familiarity with monitoring, logging, and alerting tools (eg, Azure Monitor).

Desirable

  • Experience with additional Azure services (eg, Fabric, Azure Functions, Logic Apps).
  • Knowledge of cloud cost optimisation for data platforms.
  • Understanding of data governance and regulatory compliance (eg, GDPR).
  • Experience working in regulated or professional services environments.

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