Data & Analytics Engineer

Salary

$124,700 - $207,800

Location

Austin, TX / Raleigh, NC / San Jose, CA

Posted

Today

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data & Analytics Engineer you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

Work you'll do/responsibilities

As data & analytics engineer, you will collaborate with various infrastructure teams, platforms, product, engineering and scientists, to identify requirements that will derive the creation of sensible operations to build and manage data analytics foundations. The ideal candidate is a self-motivated teammate with good problem solving and communication skills with the ability to adapt and learn quickly, provide results with limited direction, and choose the best possible operational decisions.
The role includes building and maintaining data pipelines for aggregation and post-processing as the project evolves.
Lead day-to-day operations to ensure organizational delivery of quality results.
Responsible for provisioning, enabling, scaling and maintaining our team’s data, analytics and ML infrastructures for batch and real time systems including pipelines, frameworks, tools and services in hybrid cloud.
Shepherd zero-downtime deployment process through continuous delivery practices, rapidly releasing features that provide critical and faster insights to business users.
Collaborate with the platform team by building the right tools for observability, monitoring, alerting and self-healing for the day-to-day management of analytics foundations.
Debug complex problems in distributed environment and ability to run the prod incidents efficiently to follow up with Post incident reviews.
Developing self-service tools and automation to improve engineering efficiency and the quality of services.
Excellent verbal and written communication skills.
Self-starter with forward thinking capability with strong executional track record and be accountable for business priorities.
and Cassandra.
Solid understanding of IAAC (infrastructure as a code) techniques like terraform, orchestration and tooling.
Experience scaling operations in a fast-paced and dynamic environment. Experience working in agile or evolving product environments.
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and/or technical teams, including escalating any matters that require additional attention and consideration from engagement management.
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes.

The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

7+yrs of experience designing, developing, and deploying next-generation analytical data products
Strong hands-on experience in SQL, Spark, and Scala, and data pipeline tools in a production environment (Apache Spark, Kafka, Airflow), CI/CD practices, and version control
Experience building and maintaining large-scale data pipelines with a focus on scalability, performance, reliability, and data quality
Proficiency with cloud platforms (AWS, Azure, or GCP) and modern data management and visualization platforms
Strong understanding of data warehousing, data modeling (dimensional/star schemas), and metric standardization
Experience with modern data platforms and lakehouse technologies (e.g., Iceberg, Trino, Superset)
Good understanding of data modeling, analytics, and metric
Above average communication skills in order to work directly with stakeholders.
Good problem-solving skills with the ability to investigate complex data issues and derive actionable insights in analytical world
Bachelor’s degree in economics, Finance, Statistics, Mathematics, Econometrics, or Applied Social Sciences.
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Hybrid role – On-site Tue-Wed-Thu

Preferred

Good understanding of data modeling, analytics, and metric design
Good problem-solving skills with the ability to investigate complex data issues and derive actionable insights
Exposure to AI/ML, recommendation systems, feature engineering, GenAI, RAG, or other AI-powered data products is a strong plus — role is not exclusively AI-focused
Knowledge of and experience in leveraging Applied Statistical/ML techniques
Ability to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive action.
Track record of leading organization-wide strategic initiatives or transformative analytics projects.
Master’s degree in economics, Finance, Statistics, Mathematics, Econometrics, or Applied Social Sciences.

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