Manager Data Engineering
Bluehilldevs · Location not stated
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Manager Data Engineering - Bluehill Devs | Career Page
Manager Data Engineering
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Job Openings Manager Data Engineering
About the job Manager Data Engineering
Manager of Data Engineering
With a proven track record of building high-performance teams and delivering world-class data solutions, you'll hire and mentor top data engineers, ensuring our team remains innovative and delivers high-quality projects on time. If you are passionate about data engineering and ready to significantly impact a fast-growing team significantly, this opportunity is perfect for you.
Responsibilities
- Lead, manage, and mentor data engineers to deliver high-quality software projects using open-source frameworks and Cloud Technologies, with a particular focus on Azure cloud data platforms
- Play a pivotal role in identifying, recruiting, and onboarding high-caliber data engineers to ensure continuous growth and expansion of our team.
- Leverage offshore resources and partners to augment in-house expertise and talent, ensuring a balanced global team capable of executing on multiple fronts.
- Set clear goals and performance objectives for the team, managing expectations and ensuring the timely and high-quality execution of these goals.
- Drive the design and implementation of modern cloud data architectures, with a strong emphasis on Azure based solutions, and contribute to evangelizing these technologies within the organization.
- Facilitate cross-functional collaboration with Product, QA, Data, and DevOps teams, ensuring the delivery of projects on time and with exceptional quality.
- Regularly report on progress towards goals, outlining current roadblocks, time estimations, results, and recommendations for accelerating project timelines.
- Actively participate in architecture, design, and code reviews for the data engineering team, providing constructive feedback and facilitating continuous improvement.
- Promote a DevOps culture and mindset from development, testing, and deployment perspectives, underlining the importance of swift and efficient operational execution.
- Apply architectural and engineering concepts to design solutions that meet operational requirements, including scalability, maintainability, flexibility, reliability, and availability.
- Take ownership of the management of production support SLAs, focusing on optimizing performance while minimizing cost.
- Ensure the highest data quality standards are maintained within the Azure cloud data platform, leveraging innovative strategies and technologies to ensure accuracy and consistency.
- Mentor and develop data engineers, encouraging innovation, timely project completion, and career growth.
- Act as a communicator, ensuring that team members, stakeholders, and other relevant parties are kept abreast of team activities, project statuses, and strategic decisions.
Qualifications
- 4+ years of data engineering management experience with a proven track record of leading engineering teams to deliver world-class data solutions.
- Bachelors degree in Computer Science, Engineering, or a related field of study.
- Experience in successfully building and deploying new data platforms on Azure, including Azure Data Factory and Power BI, showcasing both strategic and technical insight.
- Proven track record of hiring and recruiting tech talent locally and globally. Experience with outsourcing is a plus.
- Knowledge and experience with data engineering productivity toolchains and concepts (CI/CD, DevOps, GitHub, Jira, Confluence, Agile Scrum / Kanban, etc.)
- Experience with architectural design for performance and scalability.
- Comfortable working directly with data analytics to bridge business requirements with data engineering
- Expertise in Azure Data factory, Azure SQL, etc.
- Nice to have: Experience with future state technologies such as Azure Data Lake and data lakehouse architectures.
- Excellent troubleshooting and problem-solving skills
- Excellent communication and teamwork, and a passion for learning and innovating.
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Skills
- Azure
- Azure Data Factory
- Power BI
- GitHub
- Jira
- Confluence
- Azure SQL
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