GCP SQL - Manager

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Analyse and identify the linkages and interactions between the component parts of an entire system.
• Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
• Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
• Develop skills outside your comfort zone, and encourage others to do the same.
• Effectively mentor others.
• Use the review of work as an opportunity to deepen the expertise of team members.
• Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firms code of conduct, and independence requirements.
  
  

The Opportunity

When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Data and Analytics Engineering team you lead the design and implementation of innovative cloud data warehouse solutions. As a Manager, you guide teams in delivering exceptional client service while fostering a culture of mentorship and strategic planning. This role offers the chance to work with cutting-edge technologies like Snowflake and DBT, empowering you to drive impactful data solutions and enhance your leadership skills.

Responsibilities

• Lead data engineering initiatives using Snowflake, DBT, and GCP
• Collaborate with clients to define data strategy and requirements
• Mentor junior staff and promote a culture of learning
• Analyze data pipelines for efficiency and effectiveness
• Maintain compliance with industry standards and recommended practices
• Drive innovation through the adoption of cloud technologies
• Manage project deliverables and stakeholder expectations
• Identify opportunities for enhancing data analytics capabilities
  
  

What You Must Have

• Bachelors Degree in Engineering, Computer Applications, or related field
• 8 years of experience
• Oral and written proficiency in English required
• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA
  
  

What Sets You Apart

• Certifications in Snowflake (SnowPro Core) and DBT (DBT Fundamentals)
• Leading data migration and building enhanced ETL/ELT pipelines
• Collaborating with clients to translate business requirements
• Managing and mentoring technical teams for project success
• Skilled in handling large and complex data sets
• Understanding data quality processes and project lifecycle
• Knowledge of additional data tools like Python and Apache Spark
• Business knowledge in Financial Services, Healthcare, or Technology

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