Data Architect
Accenture Federal Services•Washington, DC
•$103,200 - $196,400
About The Position
At Accenture Federal Services, our purpose is to help the US federal government make the nation stronger and safer, and improve lives. Our 13,000+ employees are dedicated to leveraging technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. We are recognized as a Glassdoor Top 100 Best Place to Work, offering a collaborative and supportive community where you can grow, learn, and thrive through hands-on experience, certifications, and industry training. Join us to drive positive, lasting change that advances missions and the government forward.
Requirements
- Must be a U.S. Citizen with ability to obtain a Public Trust clearance.
- Bachelor’s degree in Computer Science, Engineering, Data/Information Systems, or related field.
- 8–12+ years in data engineering/architecture, with 3–5+ years architecting cloud data platforms (preferably GCP).
- Experience designing enterprise-grade data lakes, warehouses, and streaming architectures.
- Hands-on expertise with BigQuery, GCS, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
- Strong background in IAM, CMEK, VPC SC, encryption, DLP, and governance/lineage tools.
- Experience with regulatory compliance (FedRAMP, NIST 800-53, HIPAA, PCI, etc.).
- Demonstrated leadership in cross-functional technical initiatives.
- Strong skills with ELT/ETL, streaming patterns, schema evolution, CDC, and data modeling techniques.
- Experience with Terraform, CI/CD, Airflow/Composer, automated testing, and Git workflows.
- Proven ability to optimize BigQuery and GCS for performance and cost.
- Excellent communication and stakeholder engagement skills.
Nice To Haves
- GCP professional certifications (Cloud Architect, Data Engineer).
- Federal Government or regulated-industry experience.
- Kubernetes/OpenShift certifications (CKA/CKAD, RHCSA/RHCE).
- Experience with service mesh (Istio), API gateways, multi-cluster strategies, and GitOps at scale.
- Experience with SRE practices, incident response, and RCA.
- Familiarity with Databricks or AWS/Azure equivalents.
- Strong experience in Vertex AI, feature stores, model registries, and MLOps workflows.
- Experience with governance and metadata frameworks, stewardship workflows, and data mesh concepts.
- Experience with third-party tools (Turbot, CrowdStrike, Nessus, Dynatrace, Splunk).
- Advanced BigQuery and GCS performance-tuning expertise.
Responsibilities
- Define target-state data lake/lakehouse, warehouse, and streaming architectures on GCP.
- Establish data zones (raw/bronze, curated/silver, semantic/gold) and standards for ingestion, ELT/ETL, and consumption.
- Select and architect use of BigQuery, GCS, Dataproc, and Dataflow for scalable analytics and AI workloads.
- Develop canonical data models (3NF, star schema, Data Vault 2.0, wide tables).
- Apply BigQuery optimization techniques including partitioning, clustering, and materialized views.
- Implement least-privilege IAM, CMEK, VPC Service Controls, encryption, DLP, and private networking.
- Establish governance frameworks using Dataplex and Data Catalog with metadata, lineage, and data-quality controls.
- Ensure compliance with frameworks such as NIST 800-53, FedRAMP, HIPAA, PCI, and SOC 2.
- Design scalable batch and streaming pipelines leveraging Dataflow, Dataproc, Pub/Sub, and Composer.
- Integrate event-driven architectures using Cloud Functions/Run.
- Partner with Data Science teams to enable Vertex AI pipelines, feature stores, and MLOps.
- Ensure reproducible ML data pipelines with strong provenance and governance.
- Optimize BigQuery performance (slots, reservations, BI Engine) and GCS storage classes/lifecycle rules.
- Establish monitoring, logging, KPIs, and data quality standards.
- Define coding/IaC (Terraform) standards, CI/CD practices, and DevSecOps patterns.
- Maintain architecture artifacts and conduct architecture reviews.
- Mentor teams and support governed self-service analytics via semantic layers (Looker).
- Maintain architecture blueprints and reference implementations.
- Define ingestion, schema evolution, and retention standards.
- Review models, pipelines, IaC, and security designs.
- Conduct POCs, benchmarks, cost analyses, and documentation.
Benefits
- Accenture Federal Services offers a wide variety of benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
