Engineering Manager - Data Engineering

Your Role and Impact

• Job Title:** Engineering Manager - Data Engineering
• Location:** Pune, Maharashtra, India / Noida, Uttar Pradesh, India
• Experience:** 8 to 12 years
  

About The Company

Job Summary

Key Responsibilities

• Lead and manage data engineering projects, ensuring they are completed on time, within scope, and within budget.
• Develop project plans, timelines, and deliverables, and communicate them effectively to stakeholders.
• Coordinate with data engineers, data scientists, and analysts to deliver data-driven solutions that align with business objectives.
• Conduct risk assessments, identify potential project issues, and implement mitigation strategies to ensure project success.
• Monitor project progress and provide regular updates to senior management and stakeholders.
• Foster a collaborative and high-performing team environment by mentoring and guiding team members.
• Monitor compliance with industry standards and best practices in data management and engineering.
• Engage with clients to understand their data needs and translate them into actionable project goals.
• Continuously evaluate and improve project management processes and methodologies.
  

Required Skills And Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field. A Master’s degree is a plus.
• 8 to 12 years of experience in project management, with a focus on data engineering or data analytics.
• Strong knowledge of data engineering principles, tools, and best practices.
• Proven experience managing complex data projects with a track record of successful delivery.
• Excellent project management skills, including proficiency in project management methodologies and tools (e.g., Agile, Scrum, Waterfall).
• Strong leadership and team management skills, with the ability to motivate and inspire cross-functional teams.
• Exceptional communication skills, both written and verbal, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Proficiency in project management software (e.g., Jira, Trello, Microsoft Project) and data analytics tools.
• Strong problem-solving skills and a proactive mindset.
• Prior experience with managing delivery of Data Engineering projects (Fixed Price and T&M) within scope, budget, and timelines
• Why Join Us?**
• Opportunity to work with cutting-edge technology and innovative projects in data engineering.
• Collaborative and inclusive work culture that values diversity and creativity.
• Competitive salary and benefits package.
• Professional development opportunities to enhance your skills and career progression.
  

How To Apply

Your Contribution

• Job Title:** Engineering Manager - Data Engineering
• Job Location:** Pune, Maharashtra, India / Noida, Uttar Pradesh, India
• Experience Required:** 8 to 12 years
  

Roles And Responsibilities

• **Project Planning and Execution:**
• Define project scope, goals, and deliverables that support business goals in collaboration with senior management and stakeholders.
• Develop comprehensive project plans that outline tasks, timelines, and resource allocation to ensure successful project delivery.
• Manage project execution through regular reviews, updates, and adjustments to meet deadlines and budget constraints.
• **Team Coordination and Leadership:**
• Lead cross-functional project teams consisting of data engineers, data analysts, and other stakeholders to ensure effective collaboration.
• Delegate tasks and responsibilities to team members while providing guidance and support to ensure high-quality outcomes.
• Foster a positive team environment that encourages professional development and continuous improvement.
• **Stakeholder Communication:**
• Serve as the primary point of contact for stakeholders, including executives, clients, and internal teams, providing regular updates on project progress and performance.
• Identify and manage stakeholder expectations and risks, facilitating effective change management processes as needed.
• **Technical Oversight:**
• Oversee the development and architecture of data engineering solutions, ensuring they align with best practices and meet organizational standards.
• Collaborate with data engineering teams to understand data requirements, integrations, and technology stack to enable efficient data processing and analytics.
• **Quality Assurance and Risk Management:**
• Establish and maintain project quality standards, conducting regular reviews and assessments to ensure adherence to project requirements.
• Proactively identify potential risks and develop mitigation strategies to minimize impact on project timelines and deliverables.
• **Performance Monitoring and Reporting:**
• Monitor project performance using appropriate tools and techniques to measure progress and ensure alignment with objectives.
• Prepare and present project status reports, as well as key metrics and KPIs, to stakeholders and senior management.
• **Process Improvement:**
• Analyze project outcomes to identify areas for improvement and implement best practices in project management and data engineering.
• Encourage innovation and the adoption of new technologies, methodologies, and tools to enhance project efficiency and effectiveness.
• **Budget Management:**
• Manage project budgets, ensuring accurate documentation and reporting of project expenses and resource utilization.
• Work with finance and procurement teams to ensure that all financial aspects of the project comply with organizational policies.
  

Qualifications

• Bachelor's or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• Proven experience in project management within data engineering environments.
• Strong understanding of data engineering concepts, tools, and technologies.
• Excellent communication, interpersonal, and leadership skills.
• Prior experience with managing delivery of Data Engineering projects (Fixed Price and T&M) within scope, budget, and timelines
  

Desired Skills

• Proficiency in project management methodologies (e.g., Agile, Scrum, Waterfall).
• Experience with data architecture, ETL processes, and data analytics.
• Knowledge of programming languages and data manipulation tools (e.g., SQL, Python, Spark).