Data Engineering Manager
Location: Hyderabad
Experience: 8 to 12 Years
Experience:
- 8 to 12 years of data engineering experience with at least 3 years in a managerial role within a consulting or professional services environment.
- Proven experience in managing multiple complex data engineering projects simultaneously.
- Experience in leading a team of 8 to 12 professionals.
- Strong problemsolving skills and the ability to handle complex ambiguous situations.
- Exceptional project management skills with experience in Agile methodologies.
- A clientservice mindset and a desire to take on tough and challenging projects
- Effective communication skills both written and verbal
- Ability to work effectively across functions and levels; comfort collaborating with teammates in a virtual environment.
Job Description:
This position requires someone with good problemsolving business understanding and client presence. The overall professional experience of the candidate should be above 8 years. A minimum of 5 years of experience in leading and managing a client portfolio in the Data Engineering space. Should have good understanding of business operations challenges faced and business technology used across business functions.
The candidate must understand the usage of traditional and modern data Engineering technologies/tools for solving business problems and helping clients in their data journey. The candidate must have knowledge of emerging technologies for data management including data governance data quality security data integration processing and provisioning. The candidate must possess the required soft skills to work with teams and lead medium to large teams.
Candidate should be comfortable with taking leadership roles in client projects presales/consulting solutions business development conversations and execution on data engineering projects.
Key Responsibilities:
- Client Engagement & Relationship Management:
- Serve as the primary point of contact for clients on data engineering projects understanding their needs challenges and goals.
- Develop and maintain strong client relationships ensuring high levels of client satisfaction and repeat business.
- Translate client requirements into actionable technical solutions and project plans.
- Project Management & Delivery:
- Oversee the delivery of data engineering projects from inception to completion ensuring projects are delivered on time within scope and within budget.
- Manage project resources timelines and risks ensuring smooth project execution and delivery.
- Collaborate with crossfunctional teams including data scientists business analysts and IT professionals to deliver comprehensive data solutions.
- Technical Leadership & Innovation:
- Lead the design development and deployment of scalable data architectures pipelines and processes tailored to client needs.
- Stay abreast of industry trends technologies and best practices and implement them in client projects to drive innovation and competitive advantage.
- Provide technical oversight and guidance to the data engineering team ensuring the adoption of best practices and highquality output.
- Team Leadership & Development:
- Lead mentor and manage a team of data engineers fostering a collaborative and highperformance culture.
- Provide professional development opportunities coaching and career growth support to team members.
- Ensure the team is equipped with the necessary skills and tools to deliver highquality consulting services.
- Data Governance & Quality Assurance:
- Implement and oversee data governance frameworks ensuring data integrity security and compliance across all client projects.
- Establish and enforce data quality standards ensuring the reliability and accuracy of data used in client solutions.
- Business Development & Consulting:
- Support business development efforts by contributing to proposals presenting solutions to prospective clients and identifying opportunities for expanding client engagements.
- Provide thought leadership in data engineering contributing to white papers webinars and conferences to enhance the company s reputation in the industry.
managerial,data integration,data governance,data engineering,management,data quality,communication skills,technical leadership,team management,relationship management,business development,project management,consulting,leadership,client-service mindset,agile methodologies