Manager, Data Engineering

Manager-Data Engineering is responsible for designing, developing and maintaining data infrastructure to support efficient data management and analytics within the organization. This 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.

This role 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 Engineering

• Lead the development and maintenance of highly scalable, reliable, and resilient systems to build mature data infrastructure and tech stack.
• Develop configuration driven, flexible, efficient, and robust data pipelines, fit for multiuse including analytics, management reporting.
• Ensure Data Governance is embedded within the data pipelines to ensure the integrity and accuracy of data.

Data Strategy

• Drive the definition of the future state data and analytics platform and lead the migration of the legacy data engineering workloads.
• Collaborate with cross-functional teams, including data scientists, data product owners, and business stakeholders to understand their data requirements and deliver high-quality data pipeline solutions.

Team Leadership and Development

• Build and lead a high-functioning, well-motivated engineering team and support them in the iterative development of high-quality solutions. Provide proactive, ongoing coaching to enable and empower team members and delivery squads.
• Foster a culture of innovation within the data engineering team, encouraging experimentation and exploration of new ideas and technologies and enforce best practices for data engineering.
• Allocate resources effectively, manage workloads, and set team goals to ensure that data engineering projects are completed on time and within budget.

Security and Compliance

• Data Security Measures: Implement data encryption, access controls, and authentication mechanisms to protect sensitive customer information and comply with data privacy regulations.
• Compliance Auditing: Conduct regular compliance audits to ensure that data storage and processing practices adhere to industry regulations and internal policies.
• Incident Response Planning: Develop and maintain an incident response plan to address data breaches and security incidents promptly.

 Tool Selection and Evaluation

• Tool Selection: Evaluate emerging data technologies and select appropriate data engineering tools, platforms, and software solutions to enhance the efficiency of data infrastructure and pipelines.
• Cost Analysis: Monitor costs associated with data engineering tools and services, adjusting as necessary to optimize budget allocation.

 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 Azure/Databricks 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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