Data Engineer, (Consultant, Data & Analytics)

Fearless•Baltimore, MD

1d•$96,132 - $162,462•Remote

About The Position

We are seeking a Data Engineer as part of our Consultant, Data & Analytics career path to design, build, and optimize scalable data infrastructure that powers analytics and decision-making for federal public health programs. In this role, you will develop secure, automated data pipelines using Python, SQL, PySpark, and Databricks while working within cloud-native platforms to ensure data is accurate, reliable, and accessible. You will collaborate with data scientists, analysts, and technical stakeholders to support diverse data needs, including work that leverages machine learning and AI tools for data gathering, analysis, and visualization, all while maintaining compliance with customer and federal data standards. This is a fully remote role. At Fearless, the consultant is responsible for leveraging data to answer business questions, develop algorithms and models, and build scalable infrastructure for managing and processing data. This role will possess and/or develop the skills to be able to span the domains of data analysts, engineers, and scientists at a practical application level of proficiency. This Consultant role will work on projects that allow them to design solutions that support decision-making, optimize operations, and enable data-driven innovation.

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.

Nice To Haves

Experience with PySpark or Databricks.
Familiarity with AI and LLM orchestration frameworks such as LangChain or other workflow automation frameworks.

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.