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

Fearless is a digital integration consultancy that combines technology, people, and organizational development to solve meaningful problems. The Senior Data Engineer will architect and implement cloud-native data platforms, pipelines, and analytics solutions while guiding technical decisions, mentoring engineers, and delivering secure, scalable solutions for public-sector and regulated-industry customers.

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
• Fosters collaboration with cross functional teams
• Coach, mentor, and develop peers in data literacy, strengthening organizational decision making
• Earn the trust of your customer and teammates by delivering world class services
• Drive accountability and delivery by ensuring project objectives are not only met on time but aligned with client priorities and Fearless standards of excellence. Anticipate risks and implement proactive solutions to keep initiatives on track
• Take ownership of risk management by monitoring deliverables across the team, identifying issues early, and coaching teammates on mitigation strategies while keeping leadership informed
• Shape client engagement and intelligence-gathering efforts by actively cultivating relationships with stakeholders, synthesizing insights across the client organization and partner ecosystem, and providing Fearless leaders with actionable recommendations that inform strategy and strengthen delivery outcomes
• Deliver expected outcomes relative to data that enable smarter, faster, and more informed customer decisions
• Offer and implement innovative solutions that introduce advanced analytics, machine learning, and emerging technologies for greater data accuracy and insight
• Lead and align stakeholders with product and project goals that build trust and confidence in data as a strategic asset that drives customer value and Fearless success
• Serve as a trusted advisor in your area of expertise

Requirements:

• This role will possess the necessary skills at an advanced level of proficiency to drive organizational transformation by architecting scalable data platforms, building advanced machine learning solutions, and mentoring customers and teams to become data-driven organizations
• 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
• 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
• Managing Priorities & Client Alignment: Skillfully negotiates and manages conflicting priorities to strategically align decisions, enhancing service delivery and client satisfaction
• Advanced Application: You can perform the actions associated with a skill without assistance. You are recognized within your immediate organization as "a person to ask" when difficult questions regarding required skills arise
• 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