As a Data Analytics Engineer, you will apply hands-on engineering experience to deliver scalable, high-quality data and analytics solutions across complex, high-visibility initiatives. In this role, you will help translate business and user needs into practical technical solutions that support measurable outcomes for Deloitte. The ideal candidate brings strong experience in data engineering, modern cloud platforms, and cross-functional delivery, with a focus on building reliable, maintainable solutions.
Work you'll do
As a Software Specialist Engineer II on the Product Engineering team, you will be responsible for:
- Designing, developing, and maintaining data pipelines, integrations, and analytics engineering solutions across enterprise and cloud platforms
- Translating business, architecture, and data requirements into technical specifications, scalable data models, and production-ready code
- Collaborating with product, engineering, and cross-functional stakeholders to deliver incremental, testable solutions aligned to business goals
- Supporting code development, unit testing, deployment, issue resolution, and ongoing production support while meeting quality standards
- Contributing to modern engineering practices across the software development lifecycle, including Agile delivery, automation, DevSecOps, and continuous improvement
The team
Deloitte Technology Product Engineering builds and delivers digital products and platforms that support Deloitte's businesses, service lines, and internal operations. The team focuses on scalable, outcome-driven engineering and modern delivery practices to create solutions that improve how Deloitte operates and serves its stakeholders. By combining product thinking, engineering discipline, and cross-functional collaboration, Product Engineering helps drive innovation across the organization.
Location: Hyderabad & Bangalore
Shift Timings: General day shift
Qualifications
Required:
- Bachelor's degree in computer science, software engineering, information systems, or a related field
- 10+ years of experience building data engineering solutions using extract, transform, load and extract, load, transform tools such as Azure Data Factory, Alteryx, or cloud-native data integration tools
- 10+ years of experience working with data warehousing or data lake platforms such as SAP HANA, Snowflake, Azure Data Lake Storage, Amazon Redshift, or Google BigQuery
- 10+ years of experience building cloud-based engineering solutions on Microsoft Azure, Amazon Web Services, or Google Cloud Platform
- Experience using engineering tools and practices such as GitHub, Azure DevOps, SonarQube, Agile, DevSecOps, or Site Reliability Engineering
- Experience creating technical specifications and developing scalable, supportable code for data and analytics solutions
Preferred:
- Master's degree in computer science, software engineering, or a related field
- Experience supporting artificial intelligence, machine learning, or Generative Artificial Intelligence use cases
