Data Engineer, (Consultant, Data & Analytics)

Fearless is a digital integration consultancy that combines technology, people, and organizational development to solve meaningful problems. The Data Engineer Consultant will design, build, and optimize scalable data infrastructure and secure automated pipelines for federal public health analytics, while collaborating with data scientists, analysts, and technical stakeholders. The role also supports data modernization, machine learning integration, compliance, and data-driven decision-making.

Responsibilities:

• Design, build, and maintain scalable, distributed data pipelines and ETL/ELT workflows that support public health analytics
• Implement data modernization methods using APIs, machine learning technologies such as NLP, and artificial intelligence capabilities
• Build secure, fault-tolerant, compliant data infrastructure aligned with customer and federal standards
• Assemble, clean, and optimize large, complex datasets to meet functional and non-functional business 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 customer documentation requirements
• Ensure all electronic deliverables are Section 508 compliant
• Follow federal security, encryption, and records management requirements including FIPS-validated encryption, Privacy Act compliance, and NARA standards

Requirements:

• Minimum of 4 years of experience in data engineering or related roles
• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or related field, or equivalent work experience
• Ability to obtain and maintain Public Trust clearance
• Strong experience with ETL/ELT pipeline design, data modeling, workflow orchestration, and distributed data processing
• Experience with cloud-based data ecosystems such as Azure, AWS, or GCP
• Strong programming experience with Python, SQL, and Spark
• Experience integrating machine learning pipelines with data engineering workflows
• Experience working with message queuing, stream processing, and large-scale data systems
• Strong understanding of data quality, data validation, and data governance practices
• Experience with SQL and NoSQL databases such as Postgres, MySQL, MongoDB, or Cassandra
• Experience working in Agile delivery environments
• Analytical Thinking: The ability to observe and interpret information, break down complex problems into parts, identify patterns/relationships and draw logical conclusions to develop effective solutions
• Synthetic Thinking: The ability to combine different ideas, information, or concepts to create a new, complex understanding or solution by integrating disparate elements into a new, meaningful whole
• Adaptability: Comfort with change, flexibility in the face of shifting demands and resilience to setbacks
• Ownership & Accountability: Committed to taking responsibility for outcomes, ensuring that all commitments are met with a focus on enhancing service delivery
• Consultative Advising: Identifies and articulates client challenges, scopes projects and aligns recommendations to business goals and client expectations
• Communicating with Influence: Capable of crafting and delivering clear, persuasive messages that integrate data insights and structured narratives, tailored to the strategic needs of diverse audiences to drive effective decision-making
• Environmental Awareness: Maintains awareness of external dynamics, power structures within client environments as well as regulatory trends and contract requirements that influence service delivery
• Practical Application: You can complete tasks in required competency/skill-based areas as requested. Help from an expert may be necessary from time to time, but you can usually perform the skill independently
• 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, which may involve driving or flying
• Ability to communicate effectively via phone, email, and in-person, requiring clear speech, listening, and written communication skills
• Ability to move within an office environment, including reaching for files, using office equipment, and occasional light lifting (up to 10 pounds)
• Experience with PySpark or Databricks
• Familiarity with AI and LLM orchestration frameworks such as LangChain or other workflow automation frameworks