Senior Data Analytics Engineer

Position Overview

As a Senior Data Analytics Engineer at Deloitte, you will take a hands-on approach to high-visibility projects while leveraging your extensive engineering craftsmanship across multiple programming languages and modern frameworks. You will design, develop, and deploy advanced software solutions that drive customer outcomes and deliver tangible business value. Recruiting for this role ends on November 2, 2025.

You will be part of the US Deloitte Technology Product Engineering team, a modernized, cost-effective engine driving innovative digital solutions and powering Deloitte’s success with excellence.

Key Responsibilities

• Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes by developing high-quality, lean engineering solutions that solve complex problems.
• Technical Leadership and Advocacy: Serve as the technical advocate for products by ensuring code integrity, feasibility, and alignment with business and customer goals; lead requirement analysis, design, development, testing, integrations, and support.
• Engineering Craftsmanship: Maintain accountability for code design, implementation, quality, data, and ongoing operations while continuously learning new approaches and writing scalable, supportable code.
• Customer-Centric Engineering: Develop lean solutions through rapid experimentation to meet customer needs, engaging with product teams throughout the delivery process.
• Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning, delivering maintainable solutions with a learning-forward approach.
• Cross-Functional Collaboration and Integration: Work collaboratively with empowered teams including product management, experience, and delivery to balance feasibility, viability, usability, and value.
• Advanced Technical Proficiency: Leverage deep expertise in Agile, DevSecOps, and modern software engineering practices to implement daily product deployments with full automation across the SDLC.
• Domain Expertise: Quickly acquire domain-specific knowledge and translate business/user needs into technical specifications and robust code.
• Effective Communication and Influence: Articulate complex technical concepts clearly and compellingly to inspire and influence teammates and product teams.
• Engagement and Collaborative Co-Creation: Build constructive relationships with product engineering teams and customers, fostering a collaborative, co-creative environment.

Required Qualifications

• Bachelor's degree or equivalent in computer science, software engineering, or a related discipline; relevant experience is highly valued.
• Minimum 3 years of experience with data ETL/ELT tools (e.g., ADF, Alteryx, cloud-native tools) and data warehousing platforms (e.g., SAP HANA, Snowflake, ADLS, Amazon Redshift, Google Cloud BigQuery).
• Minimum 3 years of experience with cloud-native engineering using FaaS/PaaS/micro-services on platforms such as Azure, AWS, and GCP.
• Strong data engineering foundation with a deep understanding of data structures, algorithms, and code instrumentation.
• Familiarity with methodologies and tools including XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, and SonarQube.
• Experience in AI/ML and GenAI.
• Limited sponsorship may be available.
• Excellent interpersonal and organizational skills with the ability to manage complex projects and changing priorities.
• Ability to travel approximately 10% based on project needs.

Benefits & Perks

• Compensation: $84,300 - $173,300 (actual offer based on skill sets, experience, training, certifications, and other factors).
• Annual Incentive Program: Eligibility for a discretionary annual incentive program subject to performance and program rules.