Data Analytics Engineer

Position Summary

Deloitte is seeking a proactive and solutions-oriented Data Analytics Engineer (CL3) with 2.54 years of hands-on experience in data analytics and applied AI/ML techniques. This role involves leveraging strong technical foundation and business acumen to transform complex datasets into meaningful insights that guide decision-making and strategy. The ideal candidate will demonstrate expertise in modern data analytics tools like Python and SQL, and show enthusiasm for learning next-generation platforms such as Adobe Customer Journey Analytics (CJA). A passion for turning data into value, comfort in collaborating across diverse teams, and commitment to staying at the forefront of emerging analytics and AI trends are essential. The role requires excelling at translating business needs into actionable analysis, communicating findings effectively to both technical and non-technical audiences, and driving measurable outcomes through data.

What You Will Do

• Conduct data analysis and prepare reports to support business decision-making using statistical and machine learning techniques.
• Utilize Python and/or R, along with AI-powered coding tools like Cursor AI or GitHub Copilot, to accelerate scripting and enhance analytics workflows.
• Extract, clean, and transform data from various sources applying SQL and data wrangling skills to ensure data quality and readiness for analysis.
• Collaborate with team members to understand data requirements, ensure alignment to business objectives, and contribute to project deliverables.
• Participate in requirements gathering and solution workshops with stakeholders and senior analysts.
• Communicate analytical findings clearly to both technical and non-technical audiences via presentations, dashboards, or written summaries.
• Demonstrate curiosity and initiative by proactively learning new tools and technologies, such as Adobe Customer Journey Analytics (CJA), Adobe Experience Platform (AEP), and similar digital analytics solutions.
• Support ongoing enhancements to analytics processes, documentation, and team best practices.
• Foster a collaborative team culture by sharing knowledge and supporting others.

Key Responsibilities

Outcome-Driven Accountability

Align with delivering business outcomes, transforming business needs into analytical solutions, and upholding quality in analytics and code. This aligns with technical and professional skills.

Technical Leadership and Advocacy

Support technical best practices, code integrity, and active participation in key SDLC phases (requirement analysis, development, testing) in Python/R and SQL. Collaboration with senior team members aligns with the CL3 role.

Engineering Craftsmanship

Focus on clean code, adherence to standards, data wrangling, preparing documentation, and commitment to best practices. This directly supports expectations for programming, data wrangling, AI coding assistants skills, and continuous learning.

Customer-Centric Engineering

Focus on delivering what stakeholders need, rapid prototyping, experimentation, and direct engagement with business/product teams. This reflects analytical thinking and the ability to transform business needs into analytical solutions.

Incremental and Iterative Delivery

Embrace Agile methodologies, a growth mindset, and continuous improvement. This supports the commitment to continuously improving analytics workflows and contributing to maintainable, supportable solutions.

Cross-Functional Collaboration and Integration

Work collaboratively with diverse teams and integrate multiple perspectives. This matches requirements for collaboration, communication, and working across functions.

Advanced Technical Proficiency

Utilize Python/R for analytics and ML, SQL, AI coding assistants, and adopt new analytics tools like Adobe CJA. Embrace SDLC and Agile practices, encouraging continuous technical improvement per willingness to learn and technical skills requirements.

Domain Expertise

Quickly acquire business-relevant knowledge, understand data designs, and support business use cases with technical solutions. This supports domain knowledge and the ability to transform business needs into analytical solutions.

Effective Communication and Influence

Demonstrate excellent communication skills, presenting complex ideas to varying audiences (technical/non-technical), and contributing to team and stakeholder discussions.

Engagement and Collaborative Co-Creation

Build strong team and stakeholder relationships, foster a collaborative mindset, and co-create value-driven analytics/workflows, underpinning collaboration and a supportive team culture.

The Team

The US Deloitte Technology Product Engineering team drives success by delivering innovative analytics and data science solutions through a modern, scalable, and value-focused delivery model. As the firm's premier internal development team, they empower business units and internal operations to make smarter, data-driven decisions by transforming complex business needs into actionable insights and robust digital products. Leveraging advanced analytics tools, machine learning, and a responsive talent structure, this team consistently delivers measurable outcomes that enhance Deloitte's efficiency, effectiveness, and market leadership, upholding a tradition of excellence and commitment to impactful results.

Key Qualifications

• 2.54 years of professional experience in data analytics or data science.
• Proficiency in Python and/or R for analytics and machine learning.
• Strong SQL skills for data querying and transformation.
• Hands-on experience with AI-powered coding tools (e.g., Cursor AI, GitHub Copilot).
• Willingness to learn new tools such as Adobe CJA and other digital analytics platforms.
• Excellent communication and collaboration skills.
• Ability to transform business needs into analytical solutions.

Good to Have Skills

• Experience with cloud analytics (AWS, Azure, GCP).
• Exposure to unstructured data or MLOps.
• Participation in analytics competitions, hackathons, or relevant certifications.
• Domain knowledge in a relevant business vertical.

How You Will Grow

• Opportunity to work on impactful analytics projects.
• Support for ongoing professional development and learning new technologies.
• Collaborative environment with experts across analytics and business domains.

Our Purpose

Deloitte's purpose is to make an impact that matters for its people, clients, and communities. This purpose is reflected in their daily work with clients, investments, and commitments that drive positive outcomes for communities, enabling impact and value in client organizations.

Our People and Culture

An inclusive culture empowers Deloitte's people to be themselves, contribute unique perspectives, and make a difference individually and collectively. This fosters creativity and innovation to solve complex client challenges, making Deloitte a rewarding place to work.

Professional Development

Deloitte prioritizes professional growth by offering diverse learning and networking opportunities to accelerate careers and enhance leadership skills. The state-of-the-art DU: The Leadership Center in India, located in Hyderabad, symbolizes their commitment to holistic employee development.

Benefits To Help You Thrive

Deloitte's comprehensive rewards program aims to empower professionals to thrive mentally, physically, and financially. They offer a broad range of benefits to support professionals and their loved ones, with eligibility requirements varying by role, tenure, employment type, and other criteria.

Recruiting Tips

Deloitte provides recruiting tips to help candidates prepare and feel confident, from developing a standout resume to performing well in interviews.