Add your latest resume to match with open positions.

3 results for Data Scientist in Baltimore, MD

Data Engineer

Washington, DC
onsite
Temporary / Contract
55 - 60 USD / Hourly
Data Engineer – Databricks / Azure / AI Analytics You must be able to obtain and maintain a public trust clearance, Position OverviewWe are seeking a highly capable Data Engineer to design and support scalable data pipelines and analytics environments within a cloud-based Azure data platform. This role focuses on building modern data solutions using Databricks, Spark, and distributed data architectures, supporting enterprise-level analytics and AI initiatives.The ideal candidate brings hands-on expertise in Databricks engineering, cloud data pipelines, and data integration, along with strong collaboration skills to translate business requirements into technical solutions. This position offers the opportunity to work on large-scale data platforms and support advanced analytics and AI-driven workloads. Key ResponsibilitiesData Engineering & Pipeline Development<ul><li>Design, build, and optimize data pipelines using Databricks and Spark</li><li>Implement Medallion architecture and scalable data processing workflows</li><li>Develop ingestion pipelines for structured, streaming, and unstructured datasets</li></ul>Cloud & Platform Integration<ul><li>Work with Azure services (Data Factory, Storage, Functions, Log Analytics)</li><li>Integrate data across multiple sources to enable high-quality analytics</li><li>Support hybrid cloud initiatives and evolving data platforms</li></ul>Data Management & Optimization<ul><li>Ensure data quality, integrity, and accessibility across systems</li><li>Monitor pipeline performance and optimize cost, scalability, and efficiency</li><li>Support data governance, cataloging, and compliance standards</li></ul>Platform Operations & Support<ul><li>Troubleshoot performance issues, cluster stability, and configuration management</li><li>Support end-user requests and provide front-line platform support</li><li>Implement monitoring, logging, and alerting solutions</li></ul>DevOps & Automation<ul><li>Develop and maintain CI/CD pipelines and infrastructure-as-code (IaC)</li><li>Automate deployment and data workflows for improved efficiency</li><li>Support continuous delivery within Agile environments</li></ul>
2026-06-02T00:00:00Z

Data Engineer I

Washington, DC
remote
Temporary / Contract
44 - 47 USD / Hourly
Data Automation Engineer – AI / AWS / AzureWork Arrangement: RemoteClearance Requirement: Ability to obtain Public Trust Position OverviewWe are seeking a highly skilled Data Automation Engineer to design and implement advanced, AI-driven automation solutions across hybrid AWS and Azure environments. This role is focused on building scalable data pipelines, integrating modern cloud services, and leveraging Generative AI technologies to enhance enterprise analytics and operational workflows.The ideal candidate is a hands-on engineer with strong expertise in data engineering, cloud platforms, and automation, combined with the ability to innovate and solve complex technical challenges. This role provides the opportunity to work on mission-critical systems, supporting large-scale data processing, reporting, and AI-enabled applications. Key ResponsibilitiesData Engineering & Pipeline Development<ul><li>Design, build, and maintain scalable data pipelines using AWS services (S3, Glue, Lambda, EMR, DynamoDB)</li><li>Develop and optimize ETL/ELT workflows across hybrid AWS and Azure environments</li><li>Integrate structured, unstructured, and streaming data across enterprise systems</li></ul>AI & Automation Engineering<ul><li>Leverage Generative AI frameworks (AWS Bedrock, Azure OpenAI, LangChain, Hugging Face) to build intelligent automation</li><li>Implement solutions for embeddings, vector generation, and RAG workflows</li><li>Develop AI-driven tools for data quality, anomaly detection, and pipeline optimization</li><li>Build AI-powered copilots for monitoring, troubleshooting, and workflow automation</li></ul>Data Platform Integration & Optimization<ul><li>Engineer real-time and batch ingestion pipelines using Spark, Kafka, and Flume</li><li>Integrate enterprise platforms and CRM data into data pipelines for analytics and reporting</li><li>Optimize SQL performance through stored procedures, indexing, and query tuning</li></ul>Cloud & DevOps Practices<ul><li>Implement CI/CD pipelines using tools such as GitHub, Jenkins, or Azure DevOps</li><li>Develop infrastructure solutions using Infrastructure-as-Code (IaC)</li><li>Ensure cloud security through IAM, RBAC, encryption, and network isolation</li></ul>Collaboration & Delivery<ul><li>Partner with cross-functional teams to gather requirements and deliver solutions</li><li>Support Agile delivery processes and continuous improvement initiatives</li><li>Provide technical troubleshooting and performance optimization across data systems</li></ul>
2026-06-15T00:00:00Z

Senior Data Analytics Engineer

Herndon, VA
onsite
Permanent / Full Time
140000 - 150000 USD / Yearly
We are looking for a Senior Data Analytics Engineer to help shape and scale modern data capabilities for a real estate and property organization in Reston, Virginia. This role focuses on designing reliable data pipelines, structuring analytical datasets, and enabling high-quality reporting and advanced insights across the business. The ideal candidate brings strong engineering depth, practical analytics expertise, and the ability to turn business needs into well-architected data solutions. Responsibilities: • Design, build, and maintain scalable data pipelines that ingest, transform, and deliver trusted datasets for analytics and operational use. • Develop curated data layers using medallion-style architecture to improve data quality, accessibility, and consistency across the platform. • Create and optimize dimensional models, including fact and dimension structures, to support reporting, trend analysis, and business intelligence needs. • Use Python, PySpark, SparkSQL, and notebook-based development environments to engineer efficient data processing workflows. • Partner with business and technical stakeholders to gather requirements and translate them into practical data products and analytics solutions. • Apply data governance, security, and enterprise data management standards to protect information and support compliant data usage. • Contribute to collaborative development practices through version control, code review, and shared engineering standards using Git. • Support advanced analytics initiatives by preparing data foundations that can be used for machine learning and AI-driven use cases.
2026-06-02T00:00:00Z