Senior Data Engineer, (Senior Consultant, Data & Analytics)

Fearless is a digital integration consultancy on a mission to build a better tomorrow. They are seeking a Senior Data Engineer to design and implement enterprise-scale cloud-native data platforms supporting federal and state clients, leading technical architecture, developing scalable data pipelines, and mentoring engineers.

Responsibilities:

• Lead the architecture, design, and implementation of enterprise-scale cloud-native data platforms supporting mission-critical workloads
• Design and develop scalable data pipelines supporting structured, semi-structured, and unstructured data ingestion, transformation, and delivery
• Architect modern lakehouse and data platform solutions using Databricks, Delta Lake, AWS, and open data technologies
• Partner with customer stakeholders to understand business objectives and translate them into scalable technical solutions
• Drive architectural decisions around data modeling, governance, security, observability, scalability, and cost optimization
• Design and implement robust ETL/ELT frameworks supporting enterprise analytics and operational reporting
• Develop high-performance data processing solutions using Python, SQL, Spark, and distributed computing technologies
• Build reusable data engineering frameworks, standards, and accelerators that can be leveraged across multiple customer engagements
• Implement metadata management, data lineage, cataloging, and data quality controls to support trusted enterprise data platforms
• Develop Infrastructure as Code (IaC) and CI/CD pipelines to automate deployment, testing, and operational management of cloud data solutions
• Optimize data platforms for reliability, scalability, performance, and cloud cost efficiency
• Collaborate with solution architects, software engineers, DevOps engineers, and security teams to deliver integrated cloud-native solutions
• Lead technical design sessions, architecture reviews, and code reviews while promoting engineering excellence across delivery teams
• Mentor and coach data engineers by providing technical guidance, best practices, and career development support
• Evaluate emerging technologies and recommend innovative approaches that improve platform capabilities and customer outcomes
• Support Agile delivery teams while helping shape engineering processes and technical standards across multiple programs

Requirements:

• Minimum of 7 years of experience in data engineering or related roles
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent work experience
• Demonstrated experience architecting cloud-native data platforms in AWS environments
• Expert-level proficiency with Python, SQL, Apache Spark, and distributed data processing frameworks
• Experience designing and implementing modern data lake, lakehouse, and enterprise data platform architectures
• Experience building scalable ETL/ELT frameworks supporting large, complex datasets
• Experience implementing data governance, metadata management, data lineage, and data quality solutions
• Experience designing secure, highly available, and scalable cloud-native architectures
• Experience implementing CI/CD pipelines and Infrastructure as Code using tools such as Terraform or AWS CDK
• Strong understanding of cloud networking, security, IAM, and data platform best practices
• Demonstrated ability to lead technical initiatives and influence architecture decisions across engineering teams
• Experience partnering directly with technical and non-technical stakeholders to translate business requirements into technical solutions
• Excellent communication skills with the ability to present complex technical concepts to diverse audiences
• Hands-on experience with Databricks, Unity Catalog, Delta Lake, or similar modern lakehouse technologies
• Experience with Apache Airflow, dbt, Kafka, Snowflake, Redshift, Iceberg, or comparable modern data platforms
• Experience implementing streaming and event-driven data architectures
• Experience designing Data Mesh, Data Fabric, or domain-oriented data architectures
• Experience with graph databases, vector databases, semantic search, or AI/ML data platforms
• Experience supporting analytics, machine learning, or Generative AI workloads
• Experience building data observability, monitoring, and operational excellence capabilities
• Experience supporting cloud modernization initiatives within federal or state government agencies
• Experience working in highly regulated environments requiring secure, compliant cloud architectures
• AWS Certified Data Analytics – Specialty, AWS Solutions Architect, Databricks Data Engineer Professional, or equivalent cloud certifications