Data Analytics Engineer - Software Engineer II

Data Analytics Engineer – Software Engineer II

Role Overview: We are seeking a proactive and solutions-oriented Data Analyst with 2.5–4 years of hands-on experience in data analytics and applied AI/ML techniques. In this role, you will leverage your strong technical foundation and business acumen to transform complex datasets into meaningful insights that guide decision-making and strategy. You will demonstrate expertise in modern data analytics tools (such as Python, SQL) and show enthusiasm for learning next-generation analytics platforms like Adobe Customer Journey Analytics (CJA). The ideal candidate is passionate about turning data into value, comfortable collaborating across diverse teams, and committed to staying at the forefront of emerging analytics and AI trends. You excel at translating business needs into actionable analysis, communicating findings effectively to technical and non-technical audiences, and driving measurable outcomes through data.

Work 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 such as 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.
• • oriented team culture by sharing knowledge and supporting others.

Key Responsibilities:

Outcome-Driven Accountability: Aligns with: Delivering business outcomes, transforming business needs into analytical solutions, upholding quality in analytics and code as stated in your technical and professional skills.

Technical Leadership and Advocacy: Aligns with: Supporting technical best practices, code integrity, and active participation in key SDLC phases (requirement analysis, development, testing) in Python/R, SQL, and relevant analytics tasks. Collaboration with senior team members aligns well with the CL3 role.

Engineering Craftsmanship: Aligns with: Clean code, adherence to standards, data wrangling, preparing documentation, and commitment to best practices. Directly supports your expectations for “Programming,” “Data Wrangling,” and “AI Coding Assistants” skills, and continuous learning.

Customer-Centric Engineering: Aligns with: Focus on delivering what stakeholders need, rapid prototyping, experimentation, and direct engagement with business/product teams, reflecting “Analytical Thinking” and “Ability to transform business needs into analytical solutions”.

Incremental and Iterative Delivery: Aligns with: Agile methodologies, growth mindset, and continuous improvement. Supports “Commitment to continuously improving analytics workflows” and your requirement for contributing to maintainable, supportable solutions.

Cross-Functional Collaboration and Integration: Aligns with: Collaboration, working with diverse teams, and integrating multiple perspectives. Matches “Collaboration,” “Communication,” and “Working across functions and with diverse teams.”

Advanced Technical Proficiency: Aligns with: Python/R for analytics and ML, SQL, AI coding assistants, adopting new analytics tools like Adobe CJA, and embracing SDLC and Agile practices. Encourages continuous technical improvement per your “Willingness to learn” and “Technical Skills” requirements.

Domain Expertise: Aligns with: Quickly acquiring business-relevant knowledge, understanding data designs, and supporting business use cases with technical solutions. Supports “Domain knowledge,” “Transform business needs into analytical solutions,” and related technical skills.

Effective Communication and Influence: Aligns with: Excellent communication skills, presenting complex ideas to varying audiences (technical/non-technical), and contributing to team and stakeholder discussions.

Engagement and Collaborative Co-Creation: Aligns with: Building strong team and stakeholder relationships, collaborative mindset, and co-creation of value-driven analytics/workflows—underpinning “Collaboration,” “Participation in hackathons,” and your supportive team culture.

The team: US Deloitte Technology Product Engineering drives Deloitte’s 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, we 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, our team consistently delivers measurable outcomes that enhance Deloitte’s efficiency, effectiveness, and market leadership—upholding our tradition of excellence and commitment to impactful results.

Key Qualifications:

• 2.5–4 years of professional experience in data analytics or data science
• Proficiency in Microsoft Fabric and SAC
• 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)
• Excellent communication and collaboration skills
• Ability to transform business needs into analytical solutions

Good to have skills:

2. Knowledge on BI tools like Tableau, SAP BOE is preferred

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