> Markdown version of [/jobs/ext/239935-data-operations-engineer](https://www.wearedevelopers.com/jobs/ext/239935-data-operations-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Operations Engineer - **Company:** Deloitte T.T.L. - **Location:** Austin, TX, United States - **Experience:** Expert - **Salary:** $119,000.0 - $198,400.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Data Analysis, Databases, Continuous Delivery, Data Visualization, Software Debugging, Python (Programming Language), Machine Learning, Metadata Repositories, DataOps, Spinnaker, SQL Databases, Tableau (Software), Jupyter Notebook, Cloud Platform System, Real Time Systems, Snowflake, Grafana, Apache Spark, HybridCloud, Gitlab, Kubernetes, Apache Flink, Luigi, Cassandra, Machine Learning Operations, Terraform, Splunk, Api Management, Docker, Databricks, Programming Languages - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=520267b51ab833b5 ## About the Role Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Operations 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., * Excellent verbal and written communication skills. * Self-starter with forward thinking capability with strong executional track record and be accountable for business priorities. * Hands-on experience with CI/CD pipelines and cloud environments like Gitlab, Spinnaker, Docker/Kubernetes observability using Splunk, Grafana/Data dog is a huge plus. * Proficient with one or more programming languages such as Python/Go/Rust/Java/Scala for automation and API integrations. * Experience in implementing security controls, governance processes, compliance validation, infrastructure cost analysis and optimization. * Knowledge of analytics and Applied ML stack like Apache Spark, Trino/Pinot, Iceberg, Atlas, Flink, Airflow/Luigi, Tableau, Snowflake, Databricks, MLFlow, Data Catalogs, Jupyter Notebooks, Vector database 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, Required * 10+ years of demonstrated experience in an Analytics and Strategy role. * Strong business acumen and the ability to think strategically and operationally. * Be a self-starter, driven, accountable and a high-energy team player. * Proven experience being a thought partner to cross-functional business teams offering actionable data insights and recommendations. * Demonstrated ability to influence without authority. * Excellent communication skills-able to distill complex analysis into simple, compelling narratives. Background in consulting or customer-facing, fast-paced analytical environment. * Expertise with SQL, R or Python and data visualization tools such as Tableau for full-stack data analysis, insight synthesis and presentation. * Knowledge of and experience in leveraging Applied Statistical/ML techniques. * 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 * 15+ years of demonstrated experience in an Analytics and Strategy role, preferably in the payments/fintech domain. * 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. ## Description As data operations 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. * 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 following up with Post incident reviews. * Developing self-service tools and automation to improve engineering efficiency and the quality of services. ## Related Videos - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [WeAreDevelopers LIVE - Modern DevOps for IoT Devices and More](https://www.wearedevelopers.com/videos/1805-wearedevelopers-live-modern-devops-for-iot-devices-and-more) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enabling automated 1-click customer deployments with built-in quality and security](https://www.wearedevelopers.com/videos/83-enabling-automated-1-click-customer-deployments-with-built-in-quality-and-security) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Are Code Reviews Worth It? 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