Manager, Data Engineering

This position is responsible for designing, developing and maintaining data infrastructure to support efficient data management and analytics within the organization. It plays a pivotal role in defining and building the foundational data layer, translating business initiatives into robust data models and collaborating closely with cross-functional stakeholders to design, develop, and implement scalable and resilient data pipeline solutions supporting actionable insights for senior executives and business partners.

You will also oversee a team of data engineers and be responsible for building a data centric culture within the team.

What will you do?

Data Modelling, Infrastructure and Design

• Spearhead the development and maintenance of highly scalable, reliable, and resilient systems to advance and enhance our data infrastructure and technology stack.
• Create configuration-driven, scalable, efficient, and robust data pipelines that span across various domains including employee productivity, capacity planning, incentive designs, and reporting.
• Establish and implement data quality checks within pipelines to ensure the integrity and accuracy of incoming data.

Data Strategy

• Define the future state data and analytics platform within the Azure Data ecosystem and lead the migration of legacy data engineering workloads.
• Work with cross-functional teams, including data scientists, data product owners, and business stakeholders to understand their data requirements and provide high-quality data pipeline solutions.

Team Leadership and Development

• Lead and motivate a high-functioning engineering team, providing coaching to empower members and delivery squads.
• Encourage innovation, experimentation, and best practices within the data engineering team.
• Allocate resources, manage workloads, and set goals to ensure timely, budget-compliant project completion.

Security and Compliance

• Implement data encryption, access controls, and authentication to protect sensitive information and comply with privacy regulations.
• Regularly audit compliance to ensure adherence to industry regulations and policies.
• Maintain an incident response plan for prompt action on data breaches and security incidents.

Tool Selection and Evaluation

• Tool Selection: Choose the best data engineering tools and platforms to improve infrastructure and pipelines.
• Cost Analysis: Track and adjust costs of data engineering tools and services to optimize budget.

What will you need to succeed in this role?

• Bachelor's or master's degree in computer science, Data Engineering, Software Engineering or a related field.
• 8 Years of relevant experience required. This includes experience in data engineering, data modelling, data architecture related roles.
• 3 Years of people management/Leadership experience
• Experience scaling and managing 3 person teams.

• Experience with designing and architecting data engineering pipelines using AWS/Azure Data technologies with focus on data domains and data platforms.
• Strong understanding of data structures, data modeling, and software architecture.
• Demonstrated ability to provide creative solutions to complex problems; and to translate those solutions into detailed workplans that can be effectively implemented by development teams/squads.
• A proven track-record of building and leading high-performing technology teams by example. Ability to lead, manage and inspire teams both locally and remotely, within a hybrid work environment.
• Strong problem-solving and critical-thinking abilities.
• Strong communication and collaboration skills.
• Continuous learning and staying updated with the latest advancements in Azure Databricks and data engineering are essential for success in this role.
• A result-oriented mindset, with the discipline to build operationally hardened systems, the courage to drive innovation across new capabilities and technologies, and the resilience and perseverance to 'fail forward' towards success.

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