Data Engineer
Job description
Key Responsibilities
Core Data & AI Pipeline Development
- Build, maintain, and optimize batch and streaming data pipelines to support analytics and AI workloads.
- Ingest structured, semi structured, and unstructured datasets from APIs, databases, SaaS systems, streaming feeds, and file based sources.
- Transform, clean, enrich, and standardize data using Dataflow (Apache Beam), Dataproc (Spark), BigQuery SQL, and Python.
- Deliver high quality curated datasets into BigQuery for analytics, reporting, and machine learning training.
- Build and maintain ML ready feature pipelines supporting Data Scientists and ML Engineers.
Data Quality, Governance & Operations
- Implement data quality checks, schema validation, and automated testing within pipelines.
- Monitor pipeline health and apply observability best practices using Cloud Monitoring and Cloud Logging.
- Apply governance, security, and compliance standards including IAM roles, encryption, data masking, and auditing.
- Enforce schema evolution policies, metadata management, and lineage tracking using Dataplex/Data Catalog.
- Maintain documentation for datasets, transformations, pipeline logic, and operational procedures.
Engineering & Collaboration
- Write efficient, maintainable Python, SQL, Beam, and Spark code.
- Manage ingestion flows using Pub/Sub, GCS, APIs, Datastream, and database connectors.
- Optimize BigQuery tables, partitions, clustering, materialized views, and query performance.
- Implement and maintain DAGs with Cloud Composer (Airflow).
- Troubleshoot pipeline failures, latency issues, and data quality gaps.
- Participate in code reviews, architectural discussions, and agile sprint ceremonies.
- Collaborate with Data Architects, Data Scientists, ML Engineers, and business stakeholders.
- Develop and maintain Infrastructure as Code using Terraform and CI/CD deployment pipelines.
Required Qualifications
- Must be a U.S. Citizen with ability to obtain a Public Trust clearance.
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or related technical field.
- 3–6+ years of hands on experience in data engineering or a similar technical field.
- Minimum three years of experience leading technical teams to achieve outcomes.
- Experience developing and implementing technical standards for cloud and on prem environments.
- Proven experience building production data pipelines on cloud platforms, preferably GCP.
- Hands on experience with BigQuery, GCS, Dataflow (Apache Beam), Dataproc (Spark), and Pub/Sub.
- Experience preparing ML ready datasets for model training.
- Strong background in SQL, Python, distributed data processing, and data modeling.
- Experience with governance, security, and compliance frameworks including IAM, encryption, data masking, and auditing.
- Familiarity with the following tool categories (VAEC Operational Tools):
- Google Cloud Security tools
- Google Cloud Monitoring & Logging tools
- Google Cloud Networking
- Google Storage services
Preferred Experience
- Master’s degree in a technical field.
- Previous experience in Federal Government environments.
- Knowledge of regulated environments such as FedRAMP, HIPAA, PCI, NIST 800 53, and CIS benchmarks.
- Security certifications such as CISSP or CCSP.
- Experience with Vertex AI workflows or comparable ML platforms.
- Familiarity with Dataplex, data governance frameworks, and metadata management.
- Experience with Apache Kafka or other streaming technologies.
- Experience with Datastream for change data capture (CDC).
- Knowledge of regulated industries such as public sector, healthcare, or finance.
- Strong communication skills and the ability to convey complex data concepts clearly.
- Experience with BI tools such as Looker or Looker Studio.
- Experience with third party tools such as Armis, BigFix, CrowdStrike, Tenable Nessus, Turbot, ServiceNow, Dynatrace, Splunk, and more.
- Hands on experience with DevOps tools and methodologies, including Ansible, GitHub, Jira, Terraform, CI/CD, and cloud migration tools.
- Knowledge in ML enablement, feature stores, and ML pipeline patterns.
- Experience with data quality and testing frameworks such as Great Expectations or dbt tests.
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, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia. 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.
Skills mentioned
- AI
- Ansible
- Audit
- Bigquery
- CI Cd
- Cissp
- Cloud
- Cloud Security
- Crowdstrike
- Data Engineering
- Data Governance
- Data Modeling
- Data Pipelines
- Data Quality
- Dbt
- DEVOPS
- Dynatrace
- Fedramp
- GCP
- Github
- Governance
- HIPAA
- IAM
- JIRA
- Kafka
- Looker
- Looker Studio
- Machine Learning
- Metadata Management
- Networking
- Nist
- Python
- Regulatory Compliance
- Security Clearance
- Servicenow
- Spark
- Splunk
- SQL
- Terraform
- Vertex AI

Accenture Federal Services is dedicated to empowering the U.S. federal government to navigate complex challenges and achieve superior outcomes. Our customers, including every cabinet-level department and 30 of the largest federal organizations, face the critical task of modernizing their operations to better serve the nation. We understand that legacy systems and technological debt can hinder their ability to deliver agile, responsive, and secure digital services. That's why we bring the full force of proven commercial innovation, advanced technology, and artificial intelligence to address their most pressing mission-critical priorities in national security, defense, public safety, civilian services, and military health. Our clients are striving to build a digital core that is not only smart and secure but also resilient enough to adapt to future disruptions. We partner with them to transform bold ideas into breakthrough results. Whether it's harnessing the power of data and AI to gain actionable insights, migrating to the cloud for true agility, or fortifying cybersecurity defenses, our focus is on delivering tangible value and efficiency. We help federal leaders radically reset their approach to problem-solving, enabling them to act with speed and certainty. By simplifying and streamlining operations, we help drive out costs and accelerate the transition from outdated infrastructure to powerful new platforms. Ultimately, our goal is to help create lasting value for their workforce, customers, and partners, making a tangible difference for the country and our communities.
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