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Overview

As a Manager/Architect Data Engineer, you’ll be at the forefront of large-scale digital transformation projects, designing and implementing robust, cloud-native data platforms. You will guide both strategic architecture and hands-on delivery, working closely with stakeholders to shape data ecosystems that drive business innovation and growth.

Responsibilities

Your Impact

• • Architecture & Strategy
    • Define end-to-end data architecture strategies leveraging Azure and Databricks, ensuring scalability, security, and alignment with enterprise standards.
    • Lead the selection of data technologies, frameworks, and patterns suited to each use case, considering cost, performance, and maintainability.
    • Develop and maintain architectural roadmaps for data platform modernization.
  • Solution Design & Delivery
    • Translate complex business requirements into modular, scalable data architectures.
    • Design and implement data ingestion, processing, storage, and consumption layers using modern data engineering practices.
    • Build reusable components and frameworks to accelerate future development efforts.
  • Technical Leadership
    • Provide technical leadership to engineering teams, reviewing solution designs and ensuring adherence to architectural principles.
    • Support estimation of project scope, timelines, and resources.
    • Promote data engineering best practices, including CI/CD, testing, and automation in data workflows.
  • Client Engagement & Collaboration
    • Partner with business and technical stakeholders to understand goals and co-create data-driven solutions.
    • Facilitate architecture reviews, design workshops, and technical deep dives with clients.
  • Operational Excellence
    • Monitor, optimize, and ensure the reliability and performance of deployed data solutions.
    • Lead efforts in automation, observability, and platform health monitoring.

Qualifications

Your Skills & Experience

• Proven experience designing and implementing scalable data pipelines and architectures using Azure and Databricks.
• Deep expertise with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure SQL Database.
• Strong programming skills in Python for data transformation and pipeline development.
• Experience with diverse data storage solutions: columnar (e.g., BigQuery, Redshift, Vertica), NoSQL (e.g., Cosmos DB, DynamoDB), and relational databases (e.g., SQL Server, Oracle, MySQL).
• Solid understanding of ETL/ELT processes, data modeling (dimensional, star/snowflake), and distributed computing frameworks (e.g., Spark).
• Familiarity with CI/CD pipelines, Git, and automated deployment tools.
• Effective communication and stakeholder management skills.

Additional Information

Set Yourself Apart With

• Familiarity with DevOps and DataOps practices in cloud data environments.
• Exposure to multi-cloud environments (AWS, GCP) and hybrid cloud architecture.

This position is full time and open for permanent hire and contractor modality.