Data & Analytics Architect
Key Responsibilities
Data Architecture & Strategy
- Develop and maintain endātoāend architectures for data streams, ingestion pipelines, and cloudābased processing environments.
- Define technical standards, patterns, and reusable components that support efficient data collection, integration, and operational performance.
- Provide architectural guidance for modernization efforts, including transitioning legacy workflows into Databricksānative and cloudāoptimized designs.
HandsāOn Engineering & Delivery
- Design, build, and optimize ETL/ELT pipelines for data acquisition, transformation, validation, and structured delivery.
- Lead technical prototyping and rapid development of new ingestion and processing capabilities.
- Implement quality assurance frameworks such as automated testing, CI/CD, version control workflows, and operational monitoring for reliability and reproducibility.
Data Stream Operations & Subject Matter Expertise
- Oversee and improve operational processes for highāvolume, multiāsource data streams.
- Provide engineering support for financial data workflows and other specialized data streams.
- Contribute technical expertise to modernize dashboards or analytic systems by improving upstream data pipelines and data structures.
Innovation & Platform Advancement
- Collaborate on nextāgeneration Databricks capabilities that enhance data processing, orchestration, and automation.
- Participate in platform design discussions to ensure future architectures are scalable and support emerging use cases.
Collaboration, Training & Technical Stewardship
- Partner with crossāfunctional teams to strengthen data literacy through documentation and knowledge sharing.
- Deliver training on pipeline best practices, workflow optimization, and modern engineering patterns.
- Mentor junior team members and support a community of practice centered on data engineering and cloudānative architecture.
Required Qualifications
- Bachelorās degree required; advanced degree in a related field preferred.
- Experience designing and deploying cloudābased data architectures (Azure, Databricks, AWS, SQL).
- Proficiency with modern data engineering tools and languages (Databricks, Python, R, SQL, Git, CI/CD tooling).
- Experience building largeāscale ingestion pipelines, automated reporting feeds, and cloudānative processing workflows.
- Strong ability to translate program needs into scalable, maintainable technical designs.
- Excellent communication, documentation, and stakeholder engagement skills.
Preferred Experience
- Experience working in federal, public health, or similarly complex organizational environments.
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As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.
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