Lead Data Engineer - Remote Eligible

Lead Data Engineer

Stride is an AI-Powered software engineering firm built to deliver real results. We combine elite engineering talent with cutting-edge GenAI tooling to help companies build high-quality software, modernize legacy systems, and future-proof their tech orgs. We are trusted technology partners with some of the biggest names revolutionizing the tech industry. From scaling startups to iconic Fortune 500 companies, we help our clients reach their goals by providing collaborative high-end technical consulting, agile transformation, and product delivery.

What We Are Looking For

We are seeking a Lead Data Engineer to design, build, and scale the data platforms that power analytics, reporting, and advanced data initiatives. This role bridges raw data and actionable insights by ensuring data pipelines are reliable, scalable, secure, and optimized for performance. This is a hands-on, client-facing role in a consulting environment where you will both build and lead, working closely with data scientists, analysts, product teams, and client stakeholders.

Data Platform & Pipeline Leadership

• Lead the design, development, and maintenance of scalable data pipelines and ETL/ELT processes.

• Architect and evolve cloud-based data platforms that support analytics, business intelligence, and machine learning use cases.

• Ensure data quality, integrity, availability, and consistency across systems.

• Partner with stakeholders to translate business and analytical needs into robust data solutions.

• Drive best practices for data modeling, performance optimization, and cost efficiency.

Cloud, Data & Infrastructure

• Design and manage data solutions using MySQL, MongoDB, and Snowflake.

• Build batch and event-driven data pipelines leveraging AWS services such as S3, SQS, SES, SSM, MSK, STS, and Rekognition.

• Optimize data workflows for scalability, reliability, and performance in cloud environments.

• Partner with platform and DevOps teams to ensure secure, observable, and production-ready data systems.

Cloud, Data & System Integration

• Design and integrate cloud-based services and messaging systems to support distributed architectures.

• Build and support data integrations and pipelines across relational, NoSQL, and analytics platforms.

• Ensure applications are secure, observable, and production-ready.

• Partner with DevOps and platform teams to support deployments, monitoring, and reliability.

Technical Leadership & Collaboration

• Serve as a technical leader across data initiatives, guiding architecture and implementation decisions.

• Mentor Data Engineers through code reviews, design feedback, and knowledge sharing.

• Collaborate with data scientists and analysts to ensure data is structured, discoverable, and usable.

• Lead technical discovery and feasibility assessments for new data use cases and client engagements.

• Contribute to internal data engineering standards, patterns, and documentation.

• Be a strong team player who is equal parts mentor, coach, enabler, doer, and advisor for our teams and clients.

Data Governance, Quality, & Reliability

• Establish and enforce best practices for data governance, security, privacy, and compliance.

• Implement testing, validation, and monitoring processes to ensure data accuracy and reliability.

• Monitor and troubleshoot data pipeline issues to minimize downtime and disruption.

• Document data models, workflows, and architecture to ensure transparency and knowledge sharing.

• Identify and implement automation opportunities to streamline data operations.

Client & Stakeholder Engagement

• Work directly with client stakeholders to understand data needs, constraints, and priorities.

• Communicate data architecture decisions, tradeoffs, and risks clearly and effectively.

• Support analytics demos, reporting reviews, and data-driven decision-making discussions.

• Act as a trusted data advisor in client-facing environments.

Qualifications – Must-Haves

• 6+ years of experience as a Data Engineer or in a similar role.

• Strong expertise in SQL, data modeling, and data warehousing concepts.

• Experience working with Apache Iceberg

• Hands-on experience with MySQL, MongoDB, and Snowflake.

• Proven experience building and operating data pipelines in AWS-based environments.

• Experience with ETL/ELT frameworks and orchestration tools such as Airflow or dbt.

• Strong proficiency in Python for building and maintaining scalable data pipelines, data transformations, and automation across modern cloud and analytics platforms.

• Strong understanding of data security, privacy, and governance practices.

• Must be comfortable jumping into unclear data environments/concepts (i.e. roll up sleeves and get messy)

• Experience working in Agile delivery environments.

• Excellent communication skills and comfort working in client-facing roles.

Qualifications – Nice-to-Haves

• Experience with real-time or event-driven data processing using Kafka or MSK.

• Familiarity with machine learning pipelines and analytics enablement.

• Experience with containerization or orchestration tools such as Docker or Kubernetes.

• Exposure to data cataloging, lineage, or observability tools.

• Cloud or data engineering certifications.

What Success Looks Like

• Data pipelines are reliable, scalable, and trusted across the organization.

• Analytics and data science teams are empowered with clean, well-structured data.

• Clients and stakeholders gain faster, more accurate insights to drive decisions.

• Data architecture scales as business needs evolve.

• Engineering teams benefit from clear standards, documentation, and leadership.

Stride Consulting is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment without regard to gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other category protected under the law. Stride Consulting is an equal opportunity employer; committed to a community of inclusion, and an environment free from discrimination, harassment, and retaliation.