Manager, Data Engineering

Role Overview

• Manage and Develop a High-Performing Team: Hire, mentor, and manage a team of Data Engineers. Provide clear goals, career development guidance, and ongoing performance feedback. Foster accountability, ownership, and engineering excellence.
• Own Data Engineering Execution: Oversee the design, development, and operation of scalable data pipelines and platform capabilities across our cloud data environment. Ensure reliable ingestion, transformation, and availability of structured and unstructured data.
• Enforce Platform Best Practices: Implement and enforce industry best practices for data modeling, pipeline orchestration, testing, monitoring, observability, and cost efficiency across Azure-based data infrastructure (ADLS, Databricks, and related tooling).
• Operational Excellence & Reliability: Define and manage SLAs for production data processes. Ensure high standards for data quality, reliability, and performance. Proactively identify risks and engineering bottlenecks before they impact the business.
• Collaborate Cross-Functionally: Partner with Analytics Engineering and business stakeholders (Finance, Operations, Product, Revenue) to translate business requirements into scalable technical solutions. Ensure alignment between engineering execution and business priorities.
• Support Governance & Compliance: Operationalize data governance, data protection, and compliance frameworks (including GDPR and other global requirements) in partnership with leadership. Ensure secure and responsible data management practices.
• Enable BI and AI/ML Capabilities: Ensure the data platform effectively supports analytics, reporting, machine learning, and AI workloads through well-structured, discoverable, and trusted datasets.
• Elevate Organizational Maturity: Improve engineering processes, documentation standards, code review rigor, deployment practices, and cross-team coordination to elevate the overall maturity of the Data Engineering function.
• Partner in Planning & Roadmapping: Collaborate with the Director of Data Engineering on roadmap planning, resource allocation, and prioritization to ensure successful execution of strategic initiatives.
• This role requires working overlapping hours with U.S.-based colleagues, including evening or overnight hours in India aligned to Central Standard Time (CST).
• Additional duties and responsibilities as necessary.

Requirements

• 8+ years of experience in Data Engineering or related technical fields.
• 3+ years of experience managing and developing individual contributor engineering teams.
• Established experience building and maintaining modern cloud-based data platforms (data lakes, lakehouse, or data warehouse architectures).
• Solid hands-on expertise in data pipeline development, SQL, distributed data processing, and cloud-native data services.
• Experience working with Azure-based data ecosystems (e.g., ADLS, Databricks) or similar modern cloud data platforms.
• Demonstrated ability to implement data governance, quality, and observability best practices.
• Experience supporting BI, analytics, and machine learning workloads at scale.
• Sound understanding of data modeling, ingestion frameworks, and data transformation strategies.
• Experience collaborating across distributed teams and cross-functional stakeholders.
• Excellent communication and stakeholder management skills.
• Demonstrated success hiring, mentoring, and scaling engineering talent.
• Ability to balance hands-on technical guidance with people leadership responsibilities.
• Familiarity with global data protection and compliance requirements (e.g., GDPR, SOC-2) preferred.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field preferred.

Tech Stack

• Azure
• Cloud
• SQL

Benefits

• Medical, Term & Accidental Insurance
• All Purpose Leave (casual & sick time): 12 days
• Earned Leave: 15 days
• Public Holiday: 12 days
• Generous Maternity & Paternity Leave
• Quarterly Wellness Day
• Work From Home Allowance