Data Engineering Manager

Role :: Data Engineering Manager Location :: Remote Job Description We are seeking an experienced Data Engineering Manager to lead high-performing engineering teams responsible for designing, developing, and operating scalable enterprise data platforms and solutions within the AWS ecosystem. The role combines strong technical understanding of modern data engineering technologies with people leadership, engineering governance, delivery accountability, and strategic collaboration with product and business stakeholders. The Data Engineering Manager will guide solution architecture, establish engineering standards, drive platform reliability and operational excellence, and develop engineering talent. The ideal candidate will bring prior hands-on engineering experience, remain technically current, and be capable of leading teams delivering business-critical data solutions. Key Responsibilities Engineering Leadership & Solution Design Provide technical direction and oversight for data engineering initiatives, ensuring alignment with enterprise architecture and business objectives. Review solution designs, data architectures, and technical implementation approaches, providing guidance on scalability, reliability, security, and maintainability. Partner with architects and senior engineers to evaluate technology choices, resolve design challenges, and establish appropriate engineering approaches. Guide teams developing enterprise data pipelines, integration frameworks, and analytics data platforms. Maintain sufficient technical depth to participate meaningfully in code reviews, design discussions, and complex problem resolution . Product Engineering & Delivery Management Lead engineering teams in delivering business-critical data solutions aligned with product priorities and organizational objectives. Partner with Product Managers to define initiatives, features, epics, technical priorities, and expected business outcomes. Establish delivery plans, schedules, engineering objectives, and performance metrics. Support Agile practices including sprint planning, backlog refinement, sprint reviews, and retrospectives. Identify and remove technical, organizational, and cross-team impediments impacting delivery. Drive predictable delivery while balancing engineering quality, platform stability, and business priorities . Data Platform Strategy & Engineering Excellence Contribute to the technology vision, platform strategy, architecture roadmap, and modernization initiatives for enterprise data platforms. Guide engineering teams in the effective adoption of AWS, Databricks, Spark, SQL, dbt, and associated data engineering technologies. Establish and promote engineering standards, reusable frameworks, design patterns, and development best practices. Evaluate emerging technologies and recommend improvements to platform scalability, resilience, maintainability, and operational efficiency. Collaborate with engineering teams on technology evaluations, proof-of-concept initiatives, and build-versus-buy decisions. Promote continuous improvement through automation, engineering metrics, and knowledge sharing. DevOps, Platform Reliability & Operational Excellence Establish and continuously improve SDLC, CI/CD, release management, and engineering governance practices. Promote observability, monitoring, alerting, and proactive management of data platform health. Ensure engineering teams maintain appropriate quality, testing, security, and operational standards. Support resolution of critical production incidents and act as an escalation point for complex technical or operational challenges. Drive root cause analysis, preventive improvements, and prioritization of technical debt. Establish operational metrics and continuous improvement initiatives to improve reliability and engineering effectiveness. Stakeholder & Cross-Functional Collaboration Collaborate closely with Product Managers, business stakeholders, enterprise architects, engineering leaders, and operations teams. Align engineering priorities with product strategies, business objectives, and organizational technology roadmaps. Facilitate technical discussions, design reviews, and stakeholder briefings to support informed decision-making. Build strong working relationships across engineering teams and promote consistency in technical approaches. Identify cross-team dependencies and empower teams to resolve challenges collaboratively. Communicate delivery progress, risks, resource requirements, and technology recommendations to senior stakeholders. People Leadership & Talent Development Lead and manage direct and indirect engineering teams, establishing clear accountability, performance expectations, and development objectives. Conduct regular one-on-one meetings, performance discussions, coaching sessions, and team reviews. Provide constructive feedback and career development guidance to engineers. Develop succession plans, technical capability roadmaps, and individual development plans. Foster a collaborative, inclusive, and psychologically safe environment that encourages learning, innovation, and accountability. Plan engineering capacity, identify future talent needs, and participate in recruitment and selection activities. Build and sustain high-performing engineering teams aligned with organizational goals. Technology & Vendor Management Support evaluation and selection of technology platforms, engineering tools, and external technology partners. Collaborate with technical teams to define vendor evaluation criteria and conduct proof-of-concept assessments. Participate in build-versus-buy decisions based on technical suitability, cost, scalability, and long-term business value. Support management of technology vendor relationships and associated engineering dependencies. Required Skills & Experience 9 to 10+ years of progressive experience in Information Technology, Software Engineering, or Data Engineering, including significant experience in enterprise engineering environments. Minimum 3+ years of engineering leadership or management experience, including responsibility for team performance, delivery, and talent development. Strong technical understanding of modern data engineering platforms, particularly AWS, Databricks, Apache Spark, SQL, and dbt. Prior hands-on experience in software or data engineering, with the ability to review technical designs, understand code, and guide engineering decisions. Experience leading multidisciplinary engineering teams delivering business-critical applications or data platforms. Strong understanding of data engineering architectures, ETL/ELT pipelines, distributed data processing, and data integration patterns. Experience reviewing solution architectures and guiding teams on scalability, security, reliability, and maintainability. Strong understanding of SDLC, Agile methodologies, DevOps, CI/CD, and engineering quality practices. Experience managing engineering delivery, technical roadmaps, resource planning, and multiple concurrent initiatives. Experience collaborating with Product Managers to define product priorities, engineering initiatives, and measurable outcomes. Demonstrated ability to coach, mentor, and develop engineering talent. Experience managing production support escalations, operational improvements, and platform reliability initiatives. Strong stakeholder management, communication, problem-solving, and decision-making capabilities. Ability to work effectively in complex enterprise environments with evolving priorities and cross-functional dependencies. Preferred Skills Strong hands-on background in Databricks-based data engineering solutions on AWS. Experience with Delta Lake, Medallion Architecture, and enterprise data platform modernization. Familiarity with AWS data services such as S3, Glue, IAM, and CloudWatch. Experience with Databricks Workflows, Unity Catalog, and data governance practices. Experience managing engineering budgets, vendor relationships, and technology investment decisions. Experience in Financial Services or other regulated enterprise environments. Experience leading geographically distributed engineering teams. Familiarity with AI-assisted engineering tools such as GitHub Copilot, Claude, ChatGPT, or equivalent to improve engineering productivity. Technical Skills Cloud & Data Platforms AWS Databricks Apache Spark / PySpark SQL dbt Data Engineering & ETL/ELT Architecture Engineering & DevOps SDLC & Agile Scrum CI/CD Pipelines Git / Version Control DevOps & Observability Platform Reliability & Incident Management Engineering Standards & Design Patterns Leadership & Management Engineering Team Management Technical Architecture Reviews Product & Platform Strategy Delivery & Resource Planning Stakeholder Management Talent Development & Coaching Vendor & Technology Evaluation Education Background Bachelor's degree in computer science, Information Technology, Engineering, or a related technical field OR equivalent professional experience. United IT Solutions