Consultant, Data & Analytics

Overview

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This role describes a Data Engineer position at Fearless, focusing on designing, building, and optimizing scalable data infrastructure to enable high-quality analytics. Responsibilities include developing secure, automated data pipelines; integrating and preparing large datasets; and implementing distributed data-processing workflows to ensure data is accurate, reliable, and accessible. Collaboration with data scientists, analysts, and stakeholders supports a range of data needs, including work that may involve machine learning and AI tools for data gathering, analysis, or visualization.

Technologies referenced include Python, SQL, PySpark, Databricks, and cloud-native platforms to deliver robust, fault-tolerant systems powering data-driven decision making.

This program supports the CDC’s Division of HIV Prevention in enhancing a centralized data repository and an internal Power BI dashboard that consolidates data from across the division. The focus is on improving data accessibility, quality, and usability by modernizing data architecture, building automated and scalable pipelines, and enabling interactive visualizations that help CDC staff monitor trends and make data-informed decisions.

• Design, build, and maintain scalable, distributed data pipelines and ETL/ELT workflows.
• Implement data modernization methods, including APIs, machine learning technologies (e.g., NLP), and AI capabilities.
• Build secure, fault-tolerant, compliant data infrastructure aligned with CDC and federal standards.
• Assemble, clean, and optimize large, complex datasets to meet functional and non-functional requirements.
• Develop automated processes for data delivery, data quality validation, and performance optimization.
• Utilize PySpark or Databricks to build and maintain distributed data processing pipelines.
• Collaborate with Data Scientists, Analysts, and cross-functional teams to improve data models and support data-driven decision making.
• Support ad-hoc data and analysis needs to better understand program and customer behaviors.
• Evaluate tools, technologies, and platforms for data ingestion, machine learning, orchestration, and analytics.
• Monitor data volume, data quality, data pipeline performance, and system reliability.
• Troubleshoot and resolve data and pipeline issues, performing root-cause analysis where needed.
• Build analytical tools, dashboards, and interfaces that deliver actionable insights to stakeholders.
• Document technical processes, data flows, and pipelines in accordance with CDC documentation requirements. Ensure all electronic deliverables are Section 508 compliant.
• Follow federal security, encryption, and records management requirements (FIPS-validated encryption, Privacy Act compliance, NARA standards).

• Minimum 4 years of relevant experience.
• Ability to obtain and maintain a Public Trust clearance.
• Bachelor’s degree in a relevant field (Computer Science, Data Science, Information Systems, Engineering, or related discipline).
• Strong experience with data engineering fundamentals: ETL/ELT pipeline design, data modeling, workflow orchestration, distributed data processing.
• Experience with PySpark or Databricks (highly preferred).
• Experience with cloud-based data ecosystems (Azure, AWS, or GCP).
• Familiarity with AI/LLM orchestration frameworks (e.g., Lang Chain or similar workflow automation frameworks).
• Strong programming experience with Python, SQL, and/or Spark.
• Experience integrating machine learning pipelines with data engineering workflows.
• Experience with SQL and No
  
  SQL databases (Postgres, MySQL, Mongo
  
  DB, Cassandra, etc.).
• Experience working in Agile delivery environments.
• Ability to collaborate with cross-functional teams and translate business needs into technical requirements; ability to independently learn new tools and technologies.

• Ability to sit for extended periods while working on a computer or during meetings.
• Must be able to travel occasionally to client sites or company meetings.
• Ability to communicate effectively via phone, email, and in-person.
• Ability to move within an office…