Data Engineer

Position Summary:

• Title: Data Engineer
• Duration: 12 Months – Long Term
• Location: Washington, DC 20433

Hybrid: 4 days onsite per week from day 1

• Background and Context
• The Data Engineer in this role will support programs involving one or more of the following:
• • responsible for building persistent cloud data pipelines, integrating microservices, and structuring data to power Amazon OpenSearch, Amazon Neptune (Knowledge Graphs), and Amazon SageMaker for advanced analytics.

• Scope of Work
• Pipeline Development and Implementation
• • Build continuous, event-driven streaming pipelines using Amazon EventBridge and SQS.
• • Orchestrate complex ELT transformations using EKS and Databricks.
• • Develop automated data feeds for the enterprise data platform and downstream applications.
• Solution Design and Optimization
• • Design and populate graph data models for Amazon Neptune to support entity relationship tracking.
• • Build and optimize vector indexes for Amazon OpenSearch to power the platform's AI/ML and RAG Q&A capabilities.
• • Ensure real-time or near-real-time data latency targets are met for operational dashboards.
• Stakeholder Engagement and Change Management
• • Partner directly with AI/ML Data Scientists to ensure data is properly curated, partitioned, and served for real-time model inference.
• • Support front-end developers by building reliable, performant data APIs.
• • Present pipeline architectures during technical reviews.
• Governance, Ethics, and Risk
• • Implement fine-grained, row-level Access Control to secure sensitive procurement data.
• • Set up Amazon CloudWatch and Dynatrace for continuous pipeline monitoring, alerting, and telemetry.
• • Ensure data served to AI models is clean and unbiased according to institutional guidelines.
• Documentation and Reporting
• • Maintain architectural diagrams for streaming data flows.
• • Write API endpoint documentation and AI data prep runbooks.

• Required Qualifications and Experience
• Education
• • Bachelor’s or Master’s in Computer Science, Data Engineering, or a related quantitative field.
• Certifications (Preferred)
• • AWS Certified Data Engineer – Associate or Microsoft Certified Azure Data Engineer. OR AWS ML Specialty
• Mandatory Experience
• • 5+ years building continuous data pipelines, real-time streaming architectures, and preparing data for machine learning workflows.
• Technical Knowledge
• • Expert SQL and Python.
• • Deep expertise in AWS ecosystem (EKS, Lambda, SQS, OpenSearch, Neptune, Bedrock) and Apache Spark/Databricks.
• Core Competencies
• • Strong architectural mindset, capability to handle hight-veolocity data, and enthusiasm for integrating foundational AI/ML services.

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”