Title: Data Automation Engineer
Location: Washington, DC (Remote/offsite; occasional travel to the Washington, DC metro area as needed)
Type: Contract
Compensation: $58.00/hr
Security Clearance: Must be able to obtain a Public Trust clearance
Overview
System One is seeking a Data Automation Engineer to design and implement data automation solutions primarily on AWS, with integration to selected Azure services and Generative AI capabilities. This role will build scalable data pipelines and automation solutions that integrate cloud services, enterprise tools, and GenAI to support mission-critical analytics, reporting, and customer engagement platforms.
Responsibilities
- Design and implement scalable data automation workflows using AWS services, with integration to selected Azure data platforms where required
- Develop ETL/ELT processes to ingest, transform, and move data across Amazon DynamoDB, SQL Server hosted on AWS, Azure SQL, and other enterprise data sources
- Design, develop, and support batch and near-real-time ingestion pipelines using Apache Spark and technologies such as Kafka or Flume; collaborate with search engineering to integrate pipelines with Apache Solr
- Evaluate and apply Generative AI services and frameworks (Amazon Bedrock, Azure OpenAI, Hugging Face, LangChain) to prototype and assess GenAI-assisted capabilities including:
- Metadata enrichment
- Data-quality analysis
- Structured data extraction
- Anomaly identification
- Natural-language access to enterprise data
- Recommend suitable use cases for future GenAI implementation
- Develop scalable data-processing solutions using Amazon EMR and containerized environments such as AWS Fargate or Kubernetes
- Integrate Amazon Connect customer-interaction data into analytical data stores for reporting and analytics
- Apply source control, build, containerization, and CI/CD practices using tools such as GitHub, Azure DevOps, Jenkins, and Docker
- Implement data solutions aligned with security/compliance controls (IAM, KMS encryption, VPC isolation, RBAC, firewall policies)
- Support Agile/DevOps delivery with sprint-based implementation of pipeline and AI-enabled features
Required Qualifications
- Bachelor’s degree in Computer Science or related field and 5+ years of experience in data engineering/data automation (or related discipline)
- Ability to independently design, develop, test, and troubleshoot Python- and SQL-based data pipelines in AWS (including Azure integrations where required) and clearly explain personal contributions to production implementations
- Strong hands-on experience with Apache Spark and working knowledge of at least one streaming/ingestion technology (Apache Kafka or Apache Flume)
- Hands-on experience with AWS data/integration services including several of: Amazon S3, AWS Glue, AWS Lambda, Amazon EMR, AWS Step Functions, plus at least one AWS database service
- Practical experience integrating at least one LLM platform/model service (Amazon Bedrock, Azure OpenAI Service, or an open-source model) into a Python-based workflow
- Experience integrating REST APIs/external services into Python-based pipelines and automated workflows
- Experience using Jira and one or more source-control/build/CI/CD platforms (GitHub, Azure DevOps, Jenkins)
- Strong troubleshooting and performance-optimization skills across SQL, Spark, batch pipelines, and near-real-time ingestion workflows
- Experience supporting production data platforms (SLA monitoring, incident resolution, RCA, reconciliation, performance troubleshooting, vulnerability remediation, recurring maintenance)
- Strong communication and presentation skills
- US Citizenship and ability to obtain Federal government Public Trust clearance
Preferred Qualifications
- Relevant certifications (AWS Certified Data Engineer – Associate, AWS Certified Machine Learning – Specialty, Microsoft Certified Azure AI Engineer Associate, Databricks Certified Data Engineer)
- Familiarity with RAG pipelines, embeddings, and vector search technologies (Apache Solr, Amazon OpenSearch Service, pgvector, or similar)
- Experience with multi-cloud integration (AWS and Azure)
- Experience with Docker/Kubernetes for containerized deployment, scalable data processing, and orchestration
- Experience operationalizing GenAI workflows (prompt/model configuration, evaluation, observability, monitoring, lifecycle management)
- Knowledge of data lineage/governance tools (Purview, Unity Catalog, AWS Glue Catalog)
- Familiarity with infrastructure-as-code tools (Terraform, AWS CloudFormation, Bicep)
- Experience with compliance frameworks (FedRAMP, PCI-DSS, HIPAA)
About System One
System One, and its subsidiaries including Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One offers eligible employees health and welfare benefits options including medical, dental, vision, spending accounts, life insurance, voluntary plans, and participation in a 401(k) plan.
System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law.
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Ref: 851-Rockville-S1
Ref: #851-Rockville-S1
